auxBiplot: Plots a boxplot of qVar over different categories of BiVar....

In mssm-msf-2019/BiostatsALL:

Description

It selects the N most dissimilar models among those in caret suite by maximizing the Jaccard dissimilarity between sets of models.

Usage

auxBiplot(dat, qVar, BiVar, qLab = qVar, BiLab = BiVar, model = TRUE,
  logbase = NULL, fdata = "", dir = getwd())

Arguments

dat:	database
qVar:	quantitative variable
BiVar:	categorical variable
qLab:	label for quantitative variable
BiLab:	label for categorical variable
model=TRUE,	overlays mean and SEM
logbase=NULL:	if the data was transfromed using logb, this willl allows to plot results in the naturale scale, logbase is the base used in the log transformation
fdata=”	Suffix Name for the plot; It would be composed as paste(dir,'/Boxplot',fdata,'_',qVar,'By',BiVar,sep=”)
dir=getwd()	directory to save plot and table with resutls

Examples

auxBiplot(X,qVar='IL13',BiVar='Tissue',ylab=expression(log[2]('IL-13'),model=TRUE,dir=getwd(),logbase=NULL)

mssm-msf-2019/BiostatsALL documentation built on May 22, 2019, 12:16 p.m.