GuidedSparseKmeans.S: GuidedSparseKmeans.S

In LingsongMeng/GuidedSparseKmeans: Guided Sparse K-means

Description

Selection of Tuning Parameter s in Guided Sparse K-means

Usage

GuidedSparseKmeans.S(x, z, K, s, lam, model, nstart = 20, maxiter = 15,
  nperms = 50, silence = F)

Arguments

x	Gene expression matrix, n*p (rows for subjects and columns for genes).
z	One phenotypic variable from clinical dataset, a vector.
K	Number of clusters.
s	The boundary of l1n weights, a vector.
lam	The intensity of guidance.
model	The model fitted to obtain R2, please select model from 'linear', 'logit', 'exp', 'polr','cox'.
nstart	Specify the number of starting point for K-means.
maxiter	Maximum number of iteration.
nperms	Number of permutation times
silence	Output progress or not.

Details

Select tuning parameter s via permutation in Guided Sparse K-means integrating clinical dataset with gene expression dataset.

Value

A list consisting of

nnonzerows	number of nonzero weights.
gaps	gap statistics.
segaps	statard error of gap statistics.
s	candidates of s.
s.best	the best s with largest gap.

Author(s)

Lingsong Meng

LingsongMeng/GuidedSparseKmeans documentation built on May 11, 2020, 12:29 a.m.