moGap: Gap statistic for clustering latent variables in 'moa-class'.

In mogsa: Multiple omics data integrative clustering and gene set analysis

Description

Gap statitistic is a measurement of goodness of clustering result. This is a convenient function to calculate the gap statistic of clustering "moa".

Usage

moGap(x, K.max, B = 100, cluster = c("kmeans", "hclust"), plot = TRUE, 
  dist.method = "euclidean", dist.diag = FALSE, dist.upper = FALSE, dist.p = 2, 
  hcl.method = "complete", hcl.members = NULL, 
  km.iter.max = 10, km.nstart = 10, 
  km.algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), km.trace = FALSE)

Arguments

x	An object of class moa-class returned by mbpca.
K.max	The maximum number of clusters to consider, passed to clusGap
B	The number of bootstrap, passed to clusGap
cluster	A charater string could be either "kmeans" or "hclust" to specify the clustering algorithm.
plot	Logical; whether return the gap statistic plot.
dist.method	Distance meaurement, passed to function "dist".
dist.diag	Passed to function "dist".
dist.upper	Passed to function "dist".
dist.p	Passed to function "dist".
hcl.method	Hierarchical clustering method, passed to "hclust"
hcl.members	Passed to "hclust"
km.iter.max	Maximum number of iteration in kmeans, passed to "kmeans".
km.nstart	An integer to specify how many random sets should be chosen. passed to "kmeans".
km.algorithm	Kmeans algorithm, passed to "kmeans".
km.trace	See function "kmeans".

Value

It returns a list consists of five components:

"Tab", "n", "B", "FUNcluster" - see clusGap

"nClust" - the estimated number of clusters using different method, see maxSE

Author(s)

Chen Meng

References

Tibshirani, R., Walther, G. and Hastie, T. (2001). Estimating the number of data clusters via the Gap statistic. Journal of the Royal Statistical Society B, 63, 411-423.

Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., Hornik, K.(2015). cluster: Cluster Analysis Basics and Extensions. R package version 2.0.1.

See Also

Function "clusGap" in "cluster" package Function "dist", "hclust", "kmeans"

Examples

# see examples in \code{\link{mbpca}}


data("NCI60_4arrays")
moa <- mbpca(NCI60_4arrays, ncomp = 10, k = "all", method = "globalScore", option = "lambda1", 
             center=TRUE, scale=FALSE)
gap <- moGap(moa, K.max = 12, cluster = "hcl")

genes <- moaCoef(moa)
scr <- moaScore(moa)

moa2 <- moa(NCI60_4arrays, proc.row="center_ssq1", w.data="inertia", w.row=NULL, statis=FALSE)
gap2 <- moGap(moa, K.max = 12, cluster = "hcl")

mogsa documentation built on Nov. 8, 2020, 5:41 p.m.