% Generated by roxygen2: do not edit by hand % Please edit documentation in R/GuidedSparseKmeans.S.R \name{GuidedSparseKmeans.S} \alias{GuidedSparseKmeans.S} \title{GuidedSparseKmeans.S} \usage{ GuidedSparseKmeans.S(x, z, K, s, lam, model, nstart = 20, maxiter = 15, nperms = 50, silence = F) } \arguments{ \item{x}{Gene expression matrix, n*p (rows for subjects and columns for genes).} \item{z}{One phenotypic variable from clinical dataset, a vector.} \item{K}{Number of clusters.} \item{s}{The boundary of l1n weights, a vector.} \item{lam}{The intensity of guidance.} \item{model}{The model fitted to obtain R2, please select model from 'linear', 'logit', 'exp', 'polr','cox'.} \item{nstart}{Specify the number of starting point for K-means.} \item{maxiter}{Maximum number of iteration.} \item{nperms}{Number of permutation times} \item{silence}{Output progress or not.} } \value{ A list consisting of \item{nnonzerows}{number of nonzero weights.} \item{gaps}{gap statistics.} \item{segaps}{statard error of gap statistics.} \item{s}{candidates of s.} \item{s.best}{the best s with largest gap.} } \description{ Selection of Tuning Parameter s in Guided Sparse K-means } \details{ Select tuning parameter s via permutation in Guided Sparse K-means integrating clinical dataset with gene expression dataset. } \author{ Lingsong Meng }