Package: CKLRT
Type: Package
Title: Composite Kernel Machine Regression Based on Likelihood Ratio
        Test
Version: 0.2.3
Author: Ni Zhao [aut], Haoyu Zhang [aut, cre]
Maintainer: Haoyu Zhang <andrew.haoyu@gmail.com>
Description: Composite Kernel Machine Regression based on Likelihood
        Ratio Test (CKLRT): in this package, we develop a kernel
        machine regression framework to model the overall genetic
        effect of a SNP-set, considering the possible GE interaction.
        Specifically, we use a composite kernel to specify the overall
        genetic effect via a nonparametric function and we model
        additional covariates parametrically within the regression
        framework. The composite kernel is constructed as a weighted
        average of two kernels, one corresponding to the genetic main
        effect and one corresponding to the GE interaction effect. We
        propose a likelihood ratio test (LRT) and a restricted
        likelihood ratio test (RLRT) for statistical significance. We
        derive a Monte Carlo approach for the finite sample
        distributions of LRT and RLRT statistics. (N. Zhao, H. Zhang,
        J. Clark, A. Maity, M. Wu. Composite Kernel Machine Regression
        based on Likelihood Ratio Test with Application for Combined
        Genetic and Gene-environment Interaction Effect (Submitted).)
License: GPL-3
Depends: R (>= 3.1.0),
Imports: Rcpp (>= 0.12.11), mgcv, MASS, nlme, compiler, stats
LinkingTo: RcppEigen, Rcpp
Encoding: UTF-8
RoxygenNote: 6.0.1
Repository: https://andrewhaoyu.r-universe.dev
Date/Publication: 2019-02-02 02:04:32 UTC
RemoteUrl: https://github.com/andrewhaoyu/cklrt
RemoteRef: HEAD
RemoteSha: 505a9069d2a612500736f286cd354615007c1b97
NeedsCompilation: yes
Packaged: 2026-10-11 08:58:53 UTC; root