CalcMeanVar: This function estimates the robust mean and variance using...

In rMisbeta: A Robust Missing Imputation Method for Gene Expression Data

Description

The CalcMeanVar() function estimates the robust mean and variance using beta-divergence method for RobMeanVar () function. The beta-weight function confirms that is the data contain outliers or not.The larger weights indicate the good data points and the smaller weights (near to zero) indicates the outlying data points.

Usage

CalcMeanVar(xx,Mo)

Arguments

xx	xx denotes a vector of data matrix.
Mo	Mo denotes median of xx.

Value

This function returns a data frame containing 3 components

MM	Robust mean vector produced by beta-divergence method.
VV	Robust variance produced by beta-divergence method.
WW	Weights of the each data points produced by beta-divergence method using weight function.

Author(s)

Md.Shahjaman and Md. Nurul Haque Mollah [e-mail]

References

Shahjaman M, Mollah MHM, Rahman MR, Islam SSM and Mollah NHM. Robust identification of differentially expressed genes from RNA-seq data. Genomics 2020; 112(2): 2000:2010.

Examples

nG=1000
n1=n2=5
Simdat=Sim2Group(nG,n1,n2,var0=0.1,pde=0.1) 
xx=Simdat$outmat
Datao=xx
cl=rep(c(1,2),each=n1)
MisOutdat<-OutMisDat(xx,pctOut=0.1,pctMis=0.1)
res=remat(MisOutdat,cl)
up_mat<-res$remat

rMisbeta documentation built on Jan. 13, 2021, 6:28 a.m.