Package edu.cmu.tetrad.search.utils

Class KernelUtils

java.lang.Object

edu.cmu.tetrad.search.utils.KernelUtils

public class KernelUtils
extends Object

Provides various kernel utilities.

Version:

$Id: $Id

Author:

Robert Tillman

Method Summary

Modifier and Type	Method	Description
static Matrix	constructCentralizedGramMatrix(List<Kernel> kernels, DataSet dataset, List<Node> nodes)	Constructs the centralized Gram matrix for a given vector valued sample.
static Matrix	constructGramMatrix(List<Kernel> kernels, DataSet dataset, List<Node> nodes)	Constructs Gram matrix for a given vector valued sample.
static Matrix	constructH(int m)	Constructs the projection matrix on 1/m
static Matrix	incompleteCholeskyGramMatrix(List<Kernel> kernels, DataSet dataset, List<Node> nodes, double precision)	Approximates Gram matrix using incomplete Cholesky factorization

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

constructGramMatrix

public static Matrix constructGramMatrix(List<Kernel> kernels,
 DataSet dataset,
 List<Node> nodes)

Constructs Gram matrix for a given vector valued sample. The set of kernels corresponds to the variables in the set. The output matrix is the tensor product of Gram matrices for each variable.

Parameters:

kernels - the kernels for each variable

dataset - the dataset containing each variable

nodes - the variables to construct the Gram matrix for

Returns:

a Matrix object

constructCentralizedGramMatrix

public static Matrix constructCentralizedGramMatrix(List<Kernel> kernels,
 DataSet dataset,
 List<Node> nodes)

Constructs the centralized Gram matrix for a given vector valued sample. The set of kernels corresponds to the variables in the set. The output matrix is the tensor product of Gram matrices for each variable.

Parameters:

kernels - the kernels for each variable

dataset - the dataset containing each variable

nodes - the variables to construct the Gram matrix for

Returns:

a Matrix object

constructH

public static Matrix constructH(int m)

Constructs the projection matrix on 1/m

Parameters:

m - the sample size

Returns:

a Matrix object

incompleteCholeskyGramMatrix

public static Matrix incompleteCholeskyGramMatrix(List<Kernel> kernels,
 DataSet dataset,
 List<Node> nodes,
 double precision)

Approximates Gram matrix using incomplete Cholesky factorization

Parameters:

kernels - the kernels for each variable

dataset - the dataset containing each variable

nodes - the variables to construct the Gram matrix for

precision - a double

Returns:

a Matrix object