# stabpath: Stability paths plot In s4vd: Biclustering via Sparse Singular Value Decomposition Incorporating Stability Selection

## Description

The function plots the stability path of a S4VD result

## Usage

 `1` ```stabpath(res,number) ```

## Arguments

 `res` the S4VD result `number` the bicluster for which the stability path shall be plotted

## Details

Plots the stability path for the rows and the columns regarding the last iteration of the s4vd algorithm. Note that if the pointwise error control was used or if savepath=FALSE the final selection probabilities for the rows and the columns will be plotted.

## Author(s)

Martin Sill \ [email protected]

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28``` ```# example data set according to the simulation study in Lee et al. 2010 # generate artifical data set and a correspondig biclust object u <- c(10,9,8,7,6,5,4,3,rep(2,17),rep(0,75)) v <- c(10,-10,8,-8,5,-5,rep(3,5),rep(-3,5),rep(0,34)) u <- u/sqrt(sum(u^2)) v <- v/sqrt(sum(v^2)) d <- 50 set.seed(1) X <- (d*u%*%t(v)) + matrix(rnorm(100*50),100,50) params <- info <- list() RowxNumber <- matrix(rep(FALSE,100),ncol=1) NumberxCol <- matrix(rep(FALSE,50),nrow=1) RowxNumber[u!=0,1] <- TRUE NumberxCol[1,v!=0] <- TRUE Number <- 1 ressim <- BiclustResult(params,RowxNumber,NumberxCol,Number,info) #perform s4vd biclustering ress4vd <- biclust(X,method=BCs4vd,pcerv=0.5, pceru=0.5,ss.thr=c(0.6,0.65),steps=500, pointwise=FALSE,nbiclust=1,savepath=TRUE) #perform s4vd biclustering with fast pointwise stability selection ress4vdpw <- biclust(X,method=BCs4vd,pcerv=0.5, pceru=0.5,ss.thr=c(0.6,0.65),steps=500, pointwise=TRUE,nbiclust=1) #stability paths stabpath(ress4vd,1) #selection probabilitys for the pointwise stability selection stabpath(ress4vdpw,1) ```

s4vd documentation built on May 2, 2019, 4:47 p.m.