com.bayesserver.analysis

Class HistogramDensity

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

Method Summary

Modifier and Type	Method and 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.