FOHSIC                  selects a fixed number of kernels which are
                        most associated with the outcome kernel.
HSIC                    Computes the HSIC criterion for two given
                        kernels
SKAT                    implements the sequence kernel association test
                        for GWAS data
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
forwardQ                models the forward selection event of a fixed
                        number of kernels as a succession of quadratic
                        constraints
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
