public class MultivariateGaussianVertex extends ProbabilisticDouble
ID_GENERATOR
Constructor and Description |
---|
MultivariateGaussianVertex(double mu,
double covariance) |
MultivariateGaussianVertex(DoubleVertex mu,
double covariance)
Matches a mu to a Multivariate Gaussian.
|
MultivariateGaussianVertex(DoubleVertex mu,
DoubleVertex covariance)
Matches a mu and covariance of some shape to a Multivariate Gaussian
|
MultivariateGaussianVertex(int[] shape,
DoubleVertex mu,
DoubleVertex covariance)
Multivariate gaussian distribution.
|
Modifier and Type | Method and Description |
---|---|
java.util.Map<java.lang.Long,DoubleTensor> |
dLogPdf(DoubleTensor value) |
double |
logPdf(DoubleTensor value) |
DoubleTensor |
sample(KeanuRandom random) |
calculateDualNumber, isProbabilistic, updateValue
abs, acos, asin, atan, atan2, ceil, cos, div, div, divideBy, divideBy, dLogPdf, dLogPdf, exp, floor, getDualNumber, getValue, lambda, log, logPdf, logPdf, matrixMultiply, minus, minus, multiply, multiply, observe, observe, plus, plus, pow, pow, round, setAndCascade, setAndCascade, setValue, setValue, sigmoid, sin, sum, tan, times, times, unaryMinus
dLogProb, logProb
addChild, addParent, addParents, dLogProbAtValue, equals, eval, getChildren, getConnectedGraph, getId, getParents, getRawValue, getShape, getValue, hashCode, hasValue, isObserved, lazyEval, logProbAtValue, observe, observeOwnValue, sample, setAndCascade, setParents, setParents, setValue, unobserve
public MultivariateGaussianVertex(int[] shape, DoubleVertex mu, DoubleVertex covariance)
shape
- the desired shape of the vertexmu
- the mu of the Multivariate Gaussiancovariance
- the covariance matrix of the Multivariate Gaussianpublic MultivariateGaussianVertex(DoubleVertex mu, DoubleVertex covariance)
mu
- the mu of the Multivariate Gaussiancovariance
- the covariance matrix of the Multivariate Gaussianpublic MultivariateGaussianVertex(DoubleVertex mu, double covariance)
mu
- the mu of the Multivariate Gaussiancovariance
- the scale of the identity matrixpublic MultivariateGaussianVertex(double mu, double covariance)
public double logPdf(DoubleTensor value)
logPdf
in class ContinuousVertex<DoubleTensor>
public java.util.Map<java.lang.Long,DoubleTensor> dLogPdf(DoubleTensor value)
dLogPdf
in class ContinuousVertex<DoubleTensor>
public DoubleTensor sample(KeanuRandom random)
sample
in class Vertex<DoubleTensor>
random
- source of randomness