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(AB) and tail variables are those to the right.Constructor and Description 

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 

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(AB).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(AB).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(AB).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(AB).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(AB).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(HT).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(HT).public double getMean(Variable continuousHead, Integer time)
continuousHead
 A continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).public double getVariance(Variable continuousHead, Integer time)
continuousHead
 A continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable and time (if any) from T in the expression P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).public double getWeight(Variable continuousHead, Integer timeHead, Variable continuousTail, Integer timeTail, StateContext... discrete)
continuousHead
 A continuous head variable from H in the expression P(HT).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(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable and time (if any) from T in the expression P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).continuousHeadB
 A second continuous head variable from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).continuousHeadB
 A second continuous head variable and time (if any) from H in the expression P(H) or P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable and associated time (if any) from T in the expression P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).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(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable and associated time (if any) from T in the expression P(HT).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(HT).continuousTail
 A continuous tail variable from T in the expression P(HT).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(HT).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(HT).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(HT).continuousTail
 A continuous tail variable and associated time (if any) from T in the expression P(HT).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 © 2019. All rights reserved.