public final class CLGaussian extends Object implements Distribution
Table
distribution which represents any discrete combinations, and for each combination there exists a multivariate Gaussian distribution and weight/regression coefficients. Note that head variables are those that appear to the left of the bar in the expression P(A|B) and tail variables are those to the right.Constructor and Description |
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CLGaussian(CLGaussian source)
Initializes a new instance of the
CLGaussian class, copying the source distribution. |
CLGaussian(CLGaussian source,
Integer timeShift)
Initializes a new instance of the
CLGaussian class, copying the source distribution but shifting any times by the specified number of units. |
CLGaussian(List<Variable> variables,
Integer time)
Initializes a new instance of the
CLGaussian class with the specified variables at a particular time. |
CLGaussian(List<Variable> variables,
Integer time,
HeadTail headTail)
Initializes a new instance of the
CLGaussian class with the specified variables. |
CLGaussian(List<VariableContext> variableContexts)
Initializes a new instance of the
CLGaussian class with the variables specified in [variableContexts]. |
CLGaussian(List<VariableContext> variableContexts,
HeadTail headTail)
Initializes a new instance of the
CLGaussian class with the variables specified in [variableContexts]. |
CLGaussian(Node node)
Initializes a new instance of the
CLGaussian class with the variables of a single node. |
CLGaussian(Node node,
Integer time)
Initializes a new instance of the
CLGaussian class with the variables of a single node at the specified time. |
CLGaussian(Variable variable)
Initializes a new instance of the
CLGaussian class with a single variable. |
CLGaussian(Variable[] variables)
Initializes a new instance of the
CLGaussian class with the specified variables. |
CLGaussian(VariableContext variableContext)
Initializes a new instance of the
CLGaussian class from a single VariableContext . |
CLGaussian(VariableContext[] variableContexts)
Initializes a new instance of the
CLGaussian class with [count] variables specified in [variableContexts]. |
CLGaussian(VariableContext[] variableContexts,
int count)
Initializes a new instance of the
CLGaussian class with [count] variables specified in [variableContexts]. |
CLGaussian(VariableContext[] variableContexts,
int count,
HeadTail headTail)
Initializes a new instance of the
CLGaussian class with [count] variables specified in [variableContexts]. |
CLGaussian(Variable variable,
Integer time)
Initializes a new instance of the
CLGaussian class with a single variable at the specified time. |
Modifier and Type | Method and Description |
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Distribution |
copy()
Creates a copy of the distribution.
|
Distribution |
copy(Integer timeShift)
Creates a copy of the distribution, and shifts any times associated with variables by the specified amount.
|
void |
copyFrom(CLGaussian source)
Copies the values from the [source] distribution to this instance.
|
CLGaussian |
divide(CLGaussian subset)
Creates a new distribution by dividing this instance by the [subset].
|
Distribution |
divide(Distribution subset)
Creates a new distribution by dividing this instance by the [subset].
|
double |
getCovariance(int index,
int sortedContinuousHeadA,
int sortedContinuousHeadB)
Gets the covariance of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
double |
getCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
State... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
StateContext... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
TableIterator iterator)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB)
Gets the covariance of a Gaussian distribution with no discrete variables between [continuousHeadA] and [continuousHeadB].
|
double |
getCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
State... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
StateContext... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
TableIterator iterator)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(Variable continuousHeadA,
Variable continuousHeadB)
Gets the covariance of a Gaussian distribution with no discrete variables between [continuousHeadA] and [continuousHeadB].
|
double |
getCovariance(Variable continuousHeadA,
Variable continuousHeadB,
State... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(Variable continuousHeadA,
Variable continuousHeadB,
StateContext... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
getCovariance(Variable continuousHeadA,
Variable continuousHeadB,
TableIterator iterator)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
boolean |
getLocked()
Locks or unlocks a distribution.
|
double |
getMean(int index,
int sortedContinuousHead)
Gets the mean of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
double |
getMean(Variable continuousHead)
Gets the mean value of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
double |
getMean(VariableContext continuousHead,
State... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
getMean(VariableContext continuousHead,
StateContext... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
getMean(VariableContext continuousHead,
TableIterator iterator)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the discrete combination.
|
double |
getMean(Variable continuousHead,
Integer time)
Gets the mean value of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable and time.
|
double |
getMean(Variable continuousHead,
Integer time,
State... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
getMean(Variable continuousHead,
Integer time,
StateContext... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
getMean(Variable continuousHead,
Integer time,
TableIterator iterator)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the discrete combination.
|
double |
getMean(Variable continuousHead,
State... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
getMean(Variable continuousHead,
StateContext... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
getMean(Variable continuousHead,
TableIterator iterator)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the discrete combination.
|
Distribution |
getOuter()
Returns the parent distribution, if this instance is aggregated by another distribution.
|
Node |
getOwner()
Gets the current owner, if assigned to a node.
|
VariableContextCollection |
getSortedContinuousHead()
Gets the collection of continuous head variables in the distribution, sorted by time (which may be null) and the order in which variables were created.
|
VariableContextCollection |
getSortedContinuousTail()
Gets the collection of continuous tail variables in the distribution, sorted by time (which may be null) and the order in which variables were created.
|
VariableContextCollection |
getSortedVariables()
Gets the collection of variables in the distribution, sorted by time (which may be null) and the order in which variables were created.
|
Table |
getTable()
Gets the
Table which specifies the distribution over any discrete variables. |
double |
getVariance(int index,
int sortedContinuousHead)
Gets the variance of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
double |
getVariance(Variable continuousHead)
Gets the variance of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
double |
getVariance(VariableContext continuousHead,
State... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(VariableContext continuousHead,
StateContext... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(VariableContext continuousHead,
TableIterator iterator)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(Variable continuousHead,
Integer time)
Gets the variance of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
double |
getVariance(Variable continuousHead,
Integer time,
State... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(Variable continuousHead,
Integer time,
StateContext... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(Variable continuousHead,
Integer time,
TableIterator iterator)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(Variable continuousHead,
State... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(Variable continuousHead,
StateContext... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getVariance(Variable continuousHead,
TableIterator iterator)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
getWeight(int index,
int sortedContinuousHead,
int sortedContinuousTail)
Gets the weight (regression coefficient) of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
double |
getWeight(VariableContext continuousHead,
VariableContext continuousTail,
State... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(VariableContext continuousHead,
VariableContext continuousTail,
StateContext... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(VariableContext continuousHead,
VariableContext continuousTail,
TableIterator iterator)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail)
Gets the weight/regression coefficient of a Gaussian distribution with no discrete variables between the [continuousTail] and [continuousHead].
|
double |
getWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
State... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
StateContext... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
TableIterator iterator)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(Variable continuousHead,
Variable continuousTail)
Gets the weight/regression coefficient of a Gaussian distribution with no discrete variables between the [continuousTail] and [continuousHead].
|
double |
getWeight(Variable continuousHead,
Variable continuousTail,
State... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(Variable continuousHead,
Variable continuousTail,
StateContext... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
getWeight(Variable continuousHead,
Variable continuousTail,
TableIterator iterator)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
Distribution |
instantiate(Double[] values)
Calculates the distribution which results from instantiating a number of variables.
|
CLGaussian |
instantiate(Variable variable,
double value)
Calculates the distribution which results from instantiating a particular variable.
|
CLGaussian |
instantiate(Variable variable,
double value,
Integer time)
Calculates the distribution which results from instantiating a particular variable at a specified time.
|
CLGaussian |
instantiateDiscrete(Integer[] discreteValues)
Instantiates discrete variables.
|
Table |
instantiateHead(double[] headValues,
double[] logPdf)
Instantiates all continuous head variable contexts.
|
CLGaussian |
instantiateHead(Variable variable,
double value,
Integer time)
Calculates the distribution which results from instantiating a particular continuous head variable at a specified time.
|
CLGaussian |
instantiateHead(Variable variable,
double value,
Integer time,
double[] logPdf)
Calculates the distribution which results from instantiating a particular continuous head variable at a specified time.
|
Distribution |
instantiateHeads(Double[] headValues,
double[] logPdf)
Instantiates continuous head variable contexts.
|
CLGaussian |
instantiateTails(Double[] tailValues)
Calculates the distribution which results from instantiating continuous tail variables.
|
boolean |
isReadOnly()
Indicates whether the distribution is read only.
|
void |
marginalize(CLGaussian superset)
Marginalizes (sums/integrates) the [superset] into this instance.
|
void |
marginalize(Distribution superset)
Marginalizes (integrates) the [superset] into this instance.
|
void |
marginalize(Distribution superset,
PropagationMethod propagation)
Marginalizes (integrates) the [superset] into this instance.
|
void |
marginalizeTo(Table table)
Marginalizes (sums/integrates) out all continuous variables from this instance into the specified table.
|
void |
marginalizeTo(Table table,
PropagationMethod propagation)
Marginalizes (sums/integrates) out all continuous variables from this instance into the specified table.
|
CLGaussian |
multiply(CLGaussian gaussian)
Multiplies this instance by another
CLGaussian distribution. |
Distribution |
multiply(Distribution distribution)
Multiplies this instance by another distribution.
|
void |
reset()
Resets all mean, covariance and weight entries to zero.
|
void |
setCovariance(int index,
int sortedContinuousHeadA,
int sortedContinuousHeadB,
double value)
Sets the covariance value of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
void |
setCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
double value)
Sets the covariance of a Gaussian distribution with no discrete variables between [continuousHeadA] and [continuousHeadB].
|
void |
setCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
double value,
State... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
double value,
StateContext... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
double value,
TableIterator iterator)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
double value)
Sets the covariance of a Gaussian distribution with no discrete variables between [continuousHeadA] and [continuousHeadB]
|
void |
setCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
double value,
State... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
double value,
StateContext... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
double value,
TableIterator iterator)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(Variable continuousHeadA,
Variable continuousHeadB,
double value)
Sets the covariance of a Gaussian distribution with no discrete variables between [continuousHeadA] and [continuousHeadB]
|
void |
setCovariance(Variable continuousHeadA,
Variable continuousHeadB,
double value,
State... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(Variable continuousHeadA,
Variable continuousHeadB,
double value,
StateContext... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setCovariance(Variable continuousHeadA,
Variable continuousHeadB,
double value,
TableIterator iterator)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
setLocked(boolean value)
Locks or unlocks a distribution.
|
void |
setMean(int index,
int sortedContinuousHead,
double value)
Sets the mean value of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
void |
setMean(VariableContext continuousHead,
double value,
State... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
setMean(VariableContext continuousHead,
double value,
StateContext... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
setMean(VariableContext continuousHead,
double value,
TableIterator iterator)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the discrete combination.
|
void |
setMean(Variable continuousHead,
double value)
Sets the mean value of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
void |
setMean(Variable continuousHead,
double value,
State... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
setMean(Variable continuousHead,
double value,
StateContext... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
setMean(Variable continuousHead,
double value,
TableIterator iterator)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the discrete combination.
|
void |
setMean(Variable continuousHead,
Integer time,
double value)
Sets the mean value of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
void |
setMean(Variable continuousHead,
Integer time,
double value,
State... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
setMean(Variable continuousHead,
Integer time,
double value,
StateContext... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
setMean(Variable continuousHead,
Integer time,
double value,
TableIterator iterator)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the discrete combination.
|
void |
setVariance(int index,
int sortedContinuousHead,
double value)
Sets the variance value of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
void |
setVariance(VariableContext continuousHead,
double value,
State... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(VariableContext continuousHead,
double value,
StateContext... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(VariableContext continuousHead,
double value,
TableIterator iterator)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(Variable continuousHead,
double value)
Sets the variance of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
void |
setVariance(Variable continuousHead,
double value,
State... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(Variable continuousHead,
double value,
StateContext... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(Variable continuousHead,
double value,
TableIterator iterator)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(Variable continuousHead,
Integer time,
double value)
Sets the variance of a Gaussian distribution with no discrete variables for the specified [continuousHead] variable.
|
void |
setVariance(Variable continuousHead,
Integer time,
double value,
State... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(Variable continuousHead,
Integer time,
double value,
StateContext... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setVariance(Variable continuousHead,
Integer time,
double value,
TableIterator iterator)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
setWeight(int index,
int sortedContinuousHead,
int sortedContinuousTail,
double value)
Sets the weight/regression coefficient of the Gaussian distribution at the specified [index] in the
Table of discrete combinations. |
void |
setWeight(VariableContext continuousHead,
VariableContext continuousTail,
double value,
State... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(VariableContext continuousHead,
VariableContext continuousTail,
double value,
StateContext... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(VariableContext continuousHead,
VariableContext continuousTail,
double value,
TableIterator iterator)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
double value)
Sets the weight/regression coefficient of a Gaussian distribution with no discrete variables between the [continuousTail] and [continuousHead].
|
void |
setWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
double value,
State... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
double value,
StateContext... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
double value,
TableIterator iterator)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(Variable continuousHead,
Variable continuousTail,
double value)
Sets the weight/regression coefficient of a Gaussian distribution with no discrete variables between the [continuousTail] and [continuousHead].
|
void |
setWeight(Variable continuousHead,
Variable continuousTail,
double value,
State... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(Variable continuousHead,
Variable continuousTail,
double value,
StateContext... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
setWeight(Variable continuousHead,
Variable continuousTail,
double value,
TableIterator iterator)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
timeShift(int units)
Shifts any times associated with the distribution variables by the specified number of time units.
|
String |
toString() |
public CLGaussian(List<VariableContext> variableContexts)
CLGaussian
class with the variables specified in [variableContexts].
Each variable, if it belongs to a temporal node can have an associated time. A variable is also marked as either head or tail. Head variables are those on the left, and tail variables are those on the right in the expression P(A|B).variableContexts
- The variable contexts containing the distribution variables.NullPointerException
- Raised if [variableContexts] is null.public CLGaussian(List<VariableContext> variableContexts, HeadTail headTail)
CLGaussian
class with the variables specified in [variableContexts].
Each variable, if it belongs to a temporal node can have an associated time. A variable is also marked as either head or tail. Head variables are those on the left, and tail variables are those on the right in the expression P(A|B).variableContexts
- The variable contexts containing the distribution variables.headTail
- Overrides the Head or Tail value found in each VariableContext
.NullPointerException
- Raised if [variableContexts] is null.public CLGaussian(VariableContext[] variableContexts)
CLGaussian
class with [count] variables specified in [variableContexts].
Each variable, if it belongs to a temporal node can have an associated time. A variable is also marked as either head or tail. Head variables are those on the left, and tail variables are those on the right in the expression P(A|B).variableContexts
- The variable contexts containing the distribution variables.NullPointerException
- Raised if [variableContexts] is null.public CLGaussian(VariableContext[] variableContexts, int count)
CLGaussian
class with [count] variables specified in [variableContexts].
Each variable, if it belongs to a temporal node can have an associated time. A variable is also marked as either head or tail. Head variables are those on the left, and tail variables are those on the right in the expression P(A|B).variableContexts
- The variable contexts containing the distribution variables.count
- The number of items to include from [variableContexts].NullPointerException
- Raised if [variableContexts] is null.public CLGaussian(VariableContext[] variableContexts, int count, HeadTail headTail)
CLGaussian
class with [count] variables specified in [variableContexts].
Each variable, if it belongs to a temporal node can have an associated time. A variable is also marked as either head or tail. Head variables are those on the left, and tail variables are those on the right in the expression P(A|B).variableContexts
- The variable contexts containing the distribution variables.count
- The number of items to include from [variableContexts].headTail
- Overrides the Head or Tail value found in each VariableContext
.NullPointerException
- Raised if [variableContexts] is null.public CLGaussian(Node node, Integer time)
CLGaussian
class with the variables of a single node at the specified time. Variables are assumed to be head variables.node
- The node whose variables will belong to the new distribution.time
- The time for any temporal nodes/variables.NullPointerException
- Raised if [node] is null.public CLGaussian(List<Variable> variables, Integer time)
CLGaussian
class with the specified variables at a particular time. Variables are assumed to be head variables.variables
- The variables for the new distribution.time
- The time for any temporal nodes/variables.NullPointerException
- Raised if [variables] is null.IllegalArgumentException
- Raised if an element of [variables] is null or a variable does not belong to a network.public CLGaussian(List<Variable> variables, Integer time, HeadTail headTail)
CLGaussian
class with the specified variables.variables
- The variables for the new distribution.time
- The time for any temporal nodes/variables.headTail
- Specifies whether the variables should be marked as Head or Tail.NullPointerException
- Raised if [variables] is null.IllegalArgumentException
- Raised if an element of [variables] is null or a variable does not belong to a network.public CLGaussian(Variable[] variables)
CLGaussian
class with the specified variables. Variables are assumed to be head variables.variables
- The variables for the new distribution.public CLGaussian(Node node)
CLGaussian
class with the variables of a single node. Variables are assumed to be head variables.node
- The node whose variables will belong to the new distribution.public CLGaussian(Variable variable)
CLGaussian
class with a single variable. The variable is assumed to be a head variable.variable
- The variable that will belong to the new distribution.public CLGaussian(VariableContext variableContext)
CLGaussian
class from a single VariableContext
.variableContext
- The variable context.NullPointerException
- Raised when [variableContext] is null.public CLGaussian(Variable variable, Integer time)
CLGaussian
class with a single variable at the specified time. The variable is assumed to be a head variable.variable
- The variable that will belong to the new distribution.time
- The time associated with the variable.NullPointerException
- Raised if [variable] is null.public CLGaussian(CLGaussian source)
CLGaussian
class, copying the source distribution.source
- The distribution to copy.public CLGaussian(CLGaussian source, Integer timeShift)
CLGaussian
class, copying the source distribution but shifting any times by the specified number of units.source
- The distribution to copy.timeShift
- The number of units to adjust any times associated with variables.public void reset()
public void timeShift(int units)
timeShift
in interface Distribution
units
- The number of time units to shift. Can be negative if required.public boolean getLocked()
Distribution.getLocked()
is true
or Distribution.getOwner()
is not null.getLocked
in interface Distribution
true
if locked; otherwise, false
.public void setLocked(boolean value)
Distribution.getLocked()
is true
or Distribution.getOwner()
is not null.setLocked
in interface Distribution
value
- true
if locked; otherwise, false
.public boolean isReadOnly()
Node
.isReadOnly
in interface Distribution
true
if read only; otherwise, false
.public Distribution copy()
copy
in interface Distribution
public Distribution copy(Integer timeShift)
copy
in interface Distribution
timeShift
- The amount to shift any times present in the distribution. Can be negative.public double getMean(int index, int sortedContinuousHead)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHead
- The position of the required continuous head variable.public double getMean(Variable continuousHead, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getMean(Variable continuousHead)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).public double getMean(Variable continuousHead, Integer time)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.public double getMean(Variable continuousHead, Integer time, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getMean(VariableContext continuousHead, State... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getMean(Variable continuousHead, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getMean(Variable continuousHead, Integer time, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getMean(VariableContext continuousHead, StateContext... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getMean(Variable continuousHead, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getMean(Variable continuousHead, Integer time, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getMean(VariableContext continuousHead, TableIterator iterator)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getVariance(int index, int sortedContinuousHead)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHead
- The position of the required continuous head variable.public double getVariance(Variable continuousHead, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getVariance(Variable continuousHead)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).public double getVariance(Variable continuousHead, Integer time)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.public double getVariance(Variable continuousHead, Integer time, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getVariance(VariableContext continuousHead, State... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getVariance(Variable continuousHead, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getVariance(Variable continuousHead, Integer time, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getVariance(VariableContext continuousHead, StateContext... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getVariance(Variable continuousHead, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getVariance(Variable continuousHead, Integer time, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getVariance(VariableContext continuousHead, TableIterator iterator)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getCovariance(int index, int sortedContinuousHeadA, int sortedContinuousHeadB)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHeadA
- The position of the first continuous head variable.sortedContinuousHeadB
- The position of the second continuous head variable.public double getCovariance(Variable continuousHeadA, Variable continuousHeadB, State... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getCovariance(Variable continuousHeadA, Variable continuousHeadB)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).public double getCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.public double getCovariance(Variable continuousHeadA, Variable continuousHeadB, StateContext... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, State... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, StateContext... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, State... discrete)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, StateContext... discrete)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getCovariance(Variable continuousHeadA, Variable continuousHeadB, TableIterator iterator)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, TableIterator iterator)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, TableIterator iterator)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getWeight(int index, int sortedContinuousHead, int sortedContinuousTail)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHead
- The position of the required continuous head variable.sortedContinuousTail
- The position of the required continuous tail variable.public double getWeight(Variable continuousHead, Variable continuousTail, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getWeight(VariableContext continuousHead, VariableContext continuousTail, State... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H|T).continuousTail
- A continuous tail variable and time (if any) from T in the expression P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getWeight(Variable continuousHead, Variable continuousTail, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getWeight(Variable continuousHead, Variable continuousTail)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).public double getWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.public double getWeight(VariableContext continuousHead, VariableContext continuousTail, StateContext... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H|T).continuousTail
- A continuous tail variable and time (if any) from T in the expression P(H|T).discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public double getWeight(Variable continuousHead, Variable continuousTail, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.iterator
- The discrete combination (mixture) identified by the position of the iterator.public double getWeight(VariableContext continuousHead, VariableContext continuousTail, TableIterator iterator)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setMean(int index, int sortedContinuousHead, double value)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHead
- The position of the required continuous head variable.value
- The mean value.public void setMean(Variable continuousHead, double value, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The mean value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setMean(Variable continuousHead, Integer time, double value, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The mean value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setMean(VariableContext continuousHead, double value, State... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The mean value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setMean(Variable continuousHead, double value, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The mean value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setMean(Variable continuousHead, double value)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The mean value.public void setMean(Variable continuousHead, Integer time, double value)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The mean value.public void setMean(Variable continuousHead, Integer time, double value, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The mean value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setMean(VariableContext continuousHead, double value, StateContext... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The mean value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setMean(Variable continuousHead, double value, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The mean value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setMean(Variable continuousHead, Integer time, double value, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The mean value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setMean(VariableContext continuousHead, double value, TableIterator iterator)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The mean value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setCovariance(int index, int sortedContinuousHeadA, int sortedContinuousHeadB, double value)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHeadA
- The position of the first continuous head variable.sortedContinuousHeadB
- The position of the second continuous head variable.value
- The covariance value to copy.public void setCovariance(Variable continuousHeadA, Variable continuousHeadB, double value, State... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).value
- The covariance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, double value, State... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.value
- The covariance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, double value, State... discrete)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The covariance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setCovariance(Variable continuousHeadA, Variable continuousHeadB, double value, StateContext... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).value
- The covariance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, double value, StateContext... discrete)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.value
- The covariance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, double value)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.value
- The covariance value.public void setCovariance(Variable continuousHeadA, Variable continuousHeadB, double value)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).value
- The covariance value.public void setCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, double value, StateContext... discrete)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The covariance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, double value)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The covariance value.public void setCovariance(Variable continuousHeadA, Variable continuousHeadB, double value, TableIterator iterator)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).value
- The covariance value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setCovariance(Variable continuousHeadA, Integer timeA, Variable continuousHeadB, Integer timeB, double value, TableIterator iterator)
continuousHeadA
- A continuous head variable from H in the expression P(H) or P(H|T).timeA
- The time of the first continuous head variable, or null if not a temporal variable.continuousHeadB
- A second continuous head variable from H in the expression P(H) or P(H|T).timeB
- The time of the second continuous head variable, or null if not a temporal variable.value
- The covariance value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setCovariance(VariableContext continuousHeadA, VariableContext continuousHeadB, double value, TableIterator iterator)
continuousHeadA
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).continuousHeadB
- A second continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The covariance value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setVariance(int index, int sortedContinuousHead, double value)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHead
- The position of the required continuous head variable.value
- The variance value to set.public void setVariance(Variable continuousHead, double value, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The variance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setVariance(Variable continuousHead, Integer time, double value, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The variance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setVariance(VariableContext continuousHead, double value, State... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The variance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setVariance(Variable continuousHead, double value, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The variance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setVariance(Variable continuousHead, double value)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The variance value.public void setVariance(Variable continuousHead, Integer time, double value)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The variance value.public void setVariance(Variable continuousHead, Integer time, double value, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The variance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setVariance(VariableContext continuousHead, double value, StateContext... discrete)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The variance value.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setVariance(Variable continuousHead, double value, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).value
- The variance value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setVariance(Variable continuousHead, Integer time, double value, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H) or P(H|T).time
- The time of the continuous head variable, or null if not a temporal variable.value
- The variance value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setVariance(VariableContext continuousHead, double value, TableIterator iterator)
continuousHead
- A continuous head variable and time (if any) from H in the expression P(H) or P(H|T).value
- The variance value.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setWeight(int index, int sortedContinuousHead, int sortedContinuousTail, double value)
Table
of discrete combinations.index
- The index into the discrete table of combinations. If no discrete variables are present in the distribution, index will always be 0.sortedContinuousHead
- The position of the required continuous head variable.sortedContinuousTail
- The position of the required continuous tail variable.value
- The weight to copy.public void setWeight(Variable continuousHead, Variable continuousTail, double value, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).value
- The weight/regression coefficient.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, double value, State... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.value
- The weight/regression coefficient.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setWeight(VariableContext continuousHead, VariableContext continuousTail, double value, State... discrete)
continuousHead
- A continuous head variable and associated time (if any) from H in the expression P(H|T).continuousTail
- A continuous tail variable and associated time (if any) from T in the expression P(H|T).value
- The weight/regression coefficient.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setWeight(Variable continuousHead, Variable continuousTail, double value, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).value
- The weight/regression coefficient.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setWeight(Variable continuousHead, Variable continuousTail, double value)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).value
- The weight/regression coefficient.public void setWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, double value, StateContext... discrete)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.value
- The weight/regression coefficient.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, double value)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.value
- The weight/regression coefficient.public void setWeight(VariableContext continuousHead, VariableContext continuousTail, double value, StateContext... discrete)
continuousHead
- A continuous head variable and associated time (if any) from H in the expression P(H|T).continuousTail
- A continuous tail variable and associated time (if any) from T in the expression P(H|T).value
- The weight/regression coefficient.discrete
- The discrete combination (mixture). Can be empty if this distribution has no discrete variables (i.e. the Gaussian is not a mixture of Gaussians).public void setWeight(Variable continuousHead, Variable continuousTail, double value, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H|T).continuousTail
- A continuous tail variable from T in the expression P(H|T).value
- The weight/regression coefficient.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, double value, TableIterator iterator)
continuousHead
- A continuous head variable from H in the expression P(H|T).timeHead
- The time of the continuous head variable, or null if not a temporal variable.continuousTail
- A continuous tail variable from T in the expression P(H|T).timeTail
- The time of the continuous tail variable, or null if not a temporal variable.value
- The weight/regression coefficient.iterator
- The discrete combination (mixture) identified by the position of the iterator.public void setWeight(VariableContext continuousHead, VariableContext continuousTail, double value, TableIterator iterator)
continuousHead
- A continuous head variable and associated time (if any) from H in the expression P(H|T).continuousTail
- A continuous tail variable and associated time (if any) from T in the expression P(H|T).value
- The weight/regression coefficient.iterator
- The discrete combination (mixture) identified by the position of the iterator.public VariableContextCollection getSortedVariables()
getSortedVariables
in interface Distribution
public VariableContextCollection getSortedContinuousHead()
VariableMap
public VariableContextCollection getSortedContinuousTail()
VariableMap
public Node getOwner()
getOwner
in interface Distribution
public Distribution getOuter()
Distribution
getOuter
in interface Distribution
public Table getTable()
Table
which specifies the distribution over any discrete variables.getTable
in interface Distribution
public void copyFrom(CLGaussian source)
source
- The source distribution from which values are copied.public Distribution divide(Distribution subset)
divide
in interface Distribution
subset
- The subset to divide by.NullPointerException
- Raised if [subset] is null.UnsupportedOperationException
- If subset is not a subset of variables in this instance.public CLGaussian divide(CLGaussian subset)
subset
- The subset to divide by.NullPointerException
- Raised if [subset] is null.UnsupportedOperationException
- If subset is not a subset of variables in this instance.public CLGaussian instantiateDiscrete(Integer[] discreteValues)
discreteValues
- A discrete value (or null) for each discrete variable in the Gaussian table.public Distribution instantiate(Double[] values)
instantiate
in interface Distribution
values
- The instantiated values. Entries can be null.in the distribution, however entries can be null.
public Distribution instantiateHeads(Double[] headValues, double[] logPdf)
headValues
- The value (or null) for each continuous head variable context.logPdf
- Optional array of length Table.size()
that is filled with the logged pdf values, useful when pdf values are zero.public CLGaussian instantiateTails(Double[] tailValues)
tailValues
- The value (or null) for each continuous tail.public CLGaussian instantiate(Variable variable, double value)
variable
- The variable to instantiate.value
- The instantiated value.NullPointerException
- Raised if [variable] is null.public CLGaussian instantiate(Variable variable, double value, Integer time)
variable
- The variable to instantiate.value
- The instantiated value.time
- The time associated with the variable. Can be null.NullPointerException
- Raised if [variable] is null.public CLGaussian instantiateHead(Variable variable, double value, Integer time)
variable
- The variable to instantiate.value
- The instantiated value.time
- The time associated with the variable. Can be null.NullPointerException
- Raised if [variable] is null.public CLGaussian instantiateHead(Variable variable, double value, Integer time, double[] logPdf)
variable
- The variable to instantiate.value
- The instantiated value.time
- The time associated with the variable. Can be null.logPdf
- A buffer of length Table.size()
that is filled with the log of the pdf values calculated during instantiation. Can be null.NullPointerException
- Raised if [variable] is null.public Table instantiateHead(double[] headValues, double[] logPdf)
headValues
- The values for the continuous head variable contexts.logPdf
- Optional array of length Table.size()
that is filled with the logged pdf values, useful when pdf values are zero.public void marginalize(Distribution superset)
marginalize
in interface Distribution
superset
- A distribution whose variables form a superset of the variables in this instance.NullPointerException
- Raised if [superset] is null.IllegalStateException
- Raised if this instance is read only, or if any variables are no longer correctly due to modifications of the network.IllegalArgumentException
- Raised if [superset] does not contain all the variables in this instance.public void marginalize(Distribution superset, PropagationMethod propagation)
marginalize
in interface Distribution
superset
- A distribution whose variables form a superset of the variables in this instance.propagation
- The propagation method to use during marginalization.NullPointerException
- Raised if [superset] is null.IllegalStateException
- Raised if this instance is read only, or if any variables are no longer correctly due to modifications of the network.IllegalArgumentException
- Raised if [superset] does not contain all the variables in this instance.public void marginalize(CLGaussian superset)
superset
- A CLGaussian
whose variables form a superset of the variables in this instance.NullPointerException
- Raised if [superset] is null.IllegalStateException
- Raised if this instance is read only, or if any variables are no longer sorted correctly due to modifications of the network.IllegalArgumentException
- Raised if [superset] does not contain all the variables in this instance.public void marginalizeTo(Table table)
table
- A Table
whose variables form a subset of discrete variables in this instance.NullPointerException
- Raised if [table] is null.public void marginalizeTo(Table table, PropagationMethod propagation)
table
- A Table
whose variables form a subset of discrete variables in this instance.propagation
- The propagation method to use during marginalization.NullPointerException
- Raised if [table] is null.public CLGaussian multiply(CLGaussian gaussian)
CLGaussian
distribution.gaussian
- The distribution to combine.NullPointerException
- Raised if [gaussian] is null.public Distribution multiply(Distribution distribution)
multiply
in interface Distribution
distribution
- The distribution to combine.NullPointerException
- Raised if [distribution] is null.Copyright © 2023. All rights reserved.