Class GaussianProposalFunction

All Implemented Interfaces:
Function<Vector,Vector>, RealVectorFunction
Direct Known Subclasses:
HybridMCMCProposalFunction

public class GaussianProposalFunction extends ProposalFunction
A proposal generator where each perturbation is a random vector, where each element is drawn from a standard Normal distribution, multiplied by a scale matrix.

Nested classes/interfaces inherited from interface dev.nm.analysis.function.Function

Function.EvaluationException
• Constructor Summary

Constructors
Constructor
Description
GaussianProposalFunction(double[] sigma, RandomLongGenerator uniform)
Constructs a Gaussian proposal function.
GaussianProposalFunction(double sigma, int size, RandomLongGenerator uniform)
Constructs a Gaussian proposal function.
GaussianProposalFunction(Matrix scale, RandomLongGenerator uniform)
Constructs a Gaussian proposal function.
• Method Summary

Modifier and Type
Method
Description
Vector
evaluate(Vector x)
Evaluate the function f at x, where x is from the domain.

Methods inherited from class dev.nm.analysis.function.rn2rm.AbstractRealVectorFunction

dimensionOfDomain, dimensionOfRange

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• Constructor Details

• GaussianProposalFunction

public GaussianProposalFunction(Matrix scale, RandomLongGenerator uniform)
Constructs a Gaussian proposal function.
Parameters:
scale - the scale matrix by which to multiply the standard Normal vector
uniform - a RandomLongGenerator
• GaussianProposalFunction

public GaussianProposalFunction(double[] sigma, RandomLongGenerator uniform)
Constructs a Gaussian proposal function. The scale matrix is a diagonal matrix, where the elements along the diagonal correspond to the given vector.
Parameters:
sigma - the standard deviations of the individual variables
uniform - a RandomLongGenerator
• GaussianProposalFunction

public GaussianProposalFunction(double sigma, int size, RandomLongGenerator uniform)
Constructs a Gaussian proposal function. The scale matrix is the identity matrix multiplied by the given constant, sigma, the standard deviation. The components have no covariance.
Parameters:
sigma - the standard deviation
size - the size of proposals
uniform - a RandomLongGenerator
• Method Details

• evaluate

public Vector evaluate(Vector x)
Description copied from interface: Function
Evaluate the function f at x, where x is from the domain.
Parameters:
x - x
Returns:
f(x)