io.improbable.keanu.vertices.dbl.probabilistic

Class InverseGammaVertex

java.lang.Object

io.improbable.keanu.vertices.Vertex<DoubleTensor>

io.improbable.keanu.vertices.dbl.DoubleVertex

io.improbable.keanu.vertices.dbl.probabilistic.InverseGammaVertex

All Implemented Interfaces:

Variable<DoubleTensor,VertexState<DoubleTensor>>, HasShape, io.improbable.keanu.kotlin.DoubleOperators<DoubleVertex>, io.improbable.keanu.kotlin.NumberOperators<DoubleVertex>, Differentiable, ProbabilisticDouble, LogProbGraphSupplier, Observable<DoubleTensor>, Probabilistic<DoubleTensor>, Samplable<DoubleTensor>, SamplableWithManyScalars<DoubleTensor>, SamplableWithShape<DoubleTensor>

public class InverseGammaVertex
extends DoubleVertex
implements Differentiable, ProbabilisticDouble, SamplableWithManyScalars<DoubleTensor>, LogProbGraphSupplier

Constructor Summary

Constructors

Constructor and Description
InverseGammaVertex(double alpha, double beta)
InverseGammaVertex(double alpha, DoubleVertex beta)
InverseGammaVertex(DoubleVertex alpha, double beta)
InverseGammaVertex(DoubleVertex alpha, DoubleVertex beta) One to one constructor for mapping some shape of alpha and beta to alpha matching shaped Inverse Gamma.
InverseGammaVertex(long[] tensorShape, double alpha, double beta)
InverseGammaVertex(long[] tensorShape, double alpha, DoubleVertex beta)
InverseGammaVertex(long[] tensorShape, DoubleVertex alpha, double beta)
InverseGammaVertex(long[] tensorShape, DoubleVertex alpha, DoubleVertex beta) One alpha or beta or both driving an arbitrarily shaped tensor of Inverse Gamma

Method Summary

Modifier and Type	Method and Description
java.util.Map<Vertex,DoubleTensor>	dLogProb(DoubleTensor value, java.util.Set<? extends Vertex> withRespectTo) The partial derivatives of the natural log prob.
DoubleVertex	getAlpha()
DoubleVertex	getBeta()
double	logProb(DoubleTensor value) This is the natural log of the probability at the supplied value.
LogProbGraph	logProbGraph()
DoubleTensor	sampleWithShape(long[] shape, KeanuRandom random)

Methods inherited from class io.improbable.keanu.vertices.dbl.DoubleVertex

abs, acos, asin, atan, atan2, ceil, concat, cos, div, div, divideBy, divideBy, equalTo, exp, floor, getValue, greaterThan, greaterThanOrEqualTo, lambda, lambda, lessThan, lessThanOrEqualTo, loadValue, log, logGamma, matrixDeterminant, matrixInverse, matrixMultiply, max, min, minus, minus, multiply, multiply, notEqualTo, observe, observe, permute, plus, plus, pow, pow, reshape, reverseDiv, reverseMinus, round, saveValue, setAndCascade, setAndCascade, setValue, setValue, setWithMask, setWithMask, sigmoid, sin, slice, sum, sum, take, tan, times, times, toGreaterThanMask, toGreaterThanMask, toGreaterThanOrEqualToMask, toGreaterThanOrEqualToMask, toInteger, toLessThanMask, toLessThanMask, toLessThanOrEqualToMask, toLessThanOrEqualToMask, transpose, unaryMinus

Methods inherited from class io.improbable.keanu.vertices.Vertex

addChild, addParent, addParents, equals, eval, getChildren, getConnectedGraph, getDegree, getId, getIndentation, getLabel, getObservedValue, getParents, getRank, getReference, getShape, getState, getValue, hashCode, hasValue, isDifferentiable, isObserved, isProbabilistic, lazyEval, observe, observeOwnValue, print, print, removeLabel, save, setAndCascade, setLabel, setLabel, setParents, setParents, setState, setValue, toString, unobserve

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface io.improbable.keanu.vertices.dbl.Differentiable

forwardModeAutoDifferentiation, reverseModeAutoDifferentiation, withRespectToSelf

Methods inherited from interface io.improbable.keanu.vertices.dbl.probabilistic.ProbabilisticDouble

dLogPdf, dLogPdf, dLogPdf, dLogPdf, dLogPdf, dLogPdf, logPdf, logPdf, logPdf

Methods inherited from interface io.improbable.keanu.vertices.Probabilistic

dLogProb, dLogProbAtValue, dLogProbAtValue, getValue, keepOnlyProbabilisticVertices, logProbAtValue

Methods inherited from interface io.improbable.keanu.vertices.Observable

getObservedValue, isObserved, observe, unobserve

Methods inherited from interface io.improbable.keanu.vertices.Samplable

sample, sample

Methods inherited from interface io.improbable.keanu.vertices.SamplableWithManyScalars

sample, sampleManyScalars, sampleManyScalars

Methods inherited from interface io.improbable.keanu.vertices.SamplableWithShape

sampleWithShape

Methods inherited from interface io.improbable.keanu.algorithms.variational.optimizer.HasShape

getShape

Constructor Detail

InverseGammaVertex

public InverseGammaVertex(long[] tensorShape,
                          DoubleVertex alpha,
                          DoubleVertex beta)

One alpha or beta or both driving an arbitrarily shaped tensor of Inverse Gamma

If all provided parameters are scalar then the proposed shape determines the shape

Parameters:

tensorShape - the desired shape of the vertex

alpha - the alpha of the Inverse Gamma with either the same shape as specified for this vertex or alpha scalar

beta - the beta of the Inverse Gamma with either the same shape as specified for this vertex or alpha scalar

InverseGammaVertex

public InverseGammaVertex(DoubleVertex alpha,
                          DoubleVertex beta)

One to one constructor for mapping some shape of alpha and beta to alpha matching shaped Inverse Gamma.

Parameters:

alpha - the alpha of the Inverse Gamma with either the same shape as specified for this vertex or alpha scalar

beta - the beta of the Inverse Gamma with either the same shape as specified for this vertex or alpha scalar

InverseGammaVertex

public InverseGammaVertex(DoubleVertex alpha,
                          double beta)

InverseGammaVertex

public InverseGammaVertex(double alpha,
                          DoubleVertex beta)

InverseGammaVertex

public InverseGammaVertex(double alpha,
                          double beta)

InverseGammaVertex

public InverseGammaVertex(long[] tensorShape,
                          DoubleVertex alpha,
                          double beta)

InverseGammaVertex

public InverseGammaVertex(long[] tensorShape,
                          double alpha,
                          DoubleVertex beta)

InverseGammaVertex

public InverseGammaVertex(long[] tensorShape,
                          double alpha,
                          double beta)

Method Detail

getAlpha

public DoubleVertex getAlpha()

getBeta

public DoubleVertex getBeta()

logProb

public double logProb(DoubleTensor value)

Description copied from interface: Probabilistic

This is the natural log of the probability at the supplied value. In the case of continuous vertices, this is actually the log of the density, which will differ from the probability by a constant.

Specified by:

logProb in interface Probabilistic<DoubleTensor>

Parameters:

value - The supplied value.

Returns:

The natural log of the probability function at the supplied value. For continuous variables this is called the PDF (probability density function). For discrete variables this is called the PMF (probability mass function).

logProbGraph

public LogProbGraph logProbGraph()

Specified by:

logProbGraph in interface LogProbGraphSupplier

dLogProb

public java.util.Map<Vertex,DoubleTensor> dLogProb(DoubleTensor value,
                                                   java.util.Set<? extends Vertex> withRespectTo)

Description copied from interface: Probabilistic

The partial derivatives of the natural log prob.

Specified by:

dLogProb in interface Probabilistic<DoubleTensor>

Parameters:

value - at a given value

withRespectTo - list of parents to differentiate with respect to

Returns:

the partial derivatives of the log of the probability function at the supplied value. For continuous variables this is called the PDF (probability density function). For discrete variables this is called the PMF (probability mass function).

sampleWithShape

public DoubleTensor sampleWithShape(long[] shape,
                                    KeanuRandom random)

Specified by:

sampleWithShape in interface SamplableWithShape<DoubleTensor>