HistogramDensity (bayesserver 10.10 API)

java.lang.Object
- com.bayesserver.analysis.HistogramDensity

All Implemented Interfaces:

EmpiricalDensity
```
public final class HistogramDensity
extends Object
implements EmpiricalDensity
```
Represents an empirical density function built from a histogram, which can represent arbitrary univariate distributions.

Constructor Summary

Constructors
Constructor Description

HistogramDensity(List<Interval<Double>> intervals, List<Double> intervalCounts)
Constructs an empirical density function.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`cdf(double x)`	Calculates an approximate value for cdf(x).
`double`	`inverseCdf(double probability)`	Calculates an approximate value for the inverse cumulative distribution function.
`static HistogramDensity`	`learn(Iterable<WeightedValue> values, HistogramDensityOptions options)`	Learns a univariate empirical density from data.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - HistogramDensity
```
public HistogramDensity(List<Interval<Double>> intervals,
                        List<Double> intervalCounts)
```
    Constructs an empirical density function.
    
    Parameters:
    
    intervals - The intervals making up the approximate density.
    
    intervalCounts - The number of elements in each interval.
- Method Detail
  - inverseCdf
```
public double inverseCdf(double probability)
```
    Calculates an approximate value for the inverse cumulative distribution function.
    
    Specified by:
    
    inverseCdf in interface EmpiricalDensity
    
    Parameters:
    
    probability - The probability p at which to return x when p = Cdf(x) .
    
    Returns:
    
    The approximate inverse cdf.
  - cdf
```
public double cdf(double x)
```
    Calculates an approximate value for cdf(x).
    
    Specified by:
    
    cdf in interface EmpiricalDensity
    
    Parameters:
    
    x - The value at which to evaluate the cdf.
    
    Returns:
    
    The approximate cdf(x).
  - learn
```
public static HistogramDensity learn(Iterable<WeightedValue> values,
                                     HistogramDensityOptions options)
```
    Learns a univariate empirical density from data.
    
    Parameters:
    
    values - The values to learn from.
    
    options - Options affecting the learning process.
    
    Returns:
    
    An empirical density.