Post-Selection Inference for Nonlinear Variable Selection


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Documentation for package ‘kernelPSI’ version 1.1.1

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adaFOHSIC adaptively selects a subset of kernels in a forward fashion.
adaQ models the forward selection of the kernels for the adaptive variant
anovaLR implements a scaled variant of the maximum likelihood ratio test
FOHSIC selects a fixed number of kernels which are most associated with the outcome kernel.
forwardQ models the forward selection event of a fixed number of kernels as a succession of quadratic constraints
HSIC Computes the HSIC criterion for two given kernels
kernelPSI computes a valid significance value for the effect of the selected kernels on the outcome
maxLR implements the maximum likelihood ratio test
pcaLR generates a closure for the computation of the likelihood ratio statistic for the kernel PCA prototype.
quadHSIC Determines the quadratic form of the HSIC unbiased estimator
ridgeLR generates a closure for the computation of the likelihood ratio statistic for the ridge prototype.
sampleH samples within the acceptance region defined by the kernel selection event
SKAT implements the sequence kernel association test for GWAS data