proba_mcar_tab: Estimation of a matrix of probabilities that missing values...

In imp4p: Imputation for Proteomics

Description

This function returns a matrix of probabilities that each missing value is MCAR from specified confidence intervals.

Usage

prob.mcar.tab(tab.u,res)

Arguments

tab.u	A numeric matrix of upper bounds for missing values.
res	An output list resulting from the function estim.mix.

Value

A numeric matrix of estimated probabilities to be MCAR for missing values assuming upper bounds for them (tab.u).

Author(s)

Quentin Giai Gianetto <[e-mail]>

See Also

estim.mix

Examples

#Simulating data
res.sim=sim.data(nb.pept=2000,nb.miss=600,para=5);

#Imputation of missing values with a MCAR-devoted algorithm: here the slsa algorithm
dat.slsa=impute.slsa(tab=res.sim$dat.obs,conditions=res.sim$condition,repbio=res.sim$repbio);

#Estimation of the mixture model
res=estim.mix(tab=res.sim$dat.obs, tab.imp=dat.slsa, conditions=res.sim$condition);

#Computing probabilities to be MCAR
born=estim.bound(tab=res.sim$dat.obs,conditions=res.sim$condition);
proba=prob.mcar.tab(born$tab.upper,res);

#Histogram of probabilities to be MCAR associated to generated MCAR values
hist(proba[res.sim$list.MCAR[[1]],1],

freq=FALSE,main="Estimated probabilities to be MCAR for known MCAR values",xlab="",col=2);

imp4p documentation built on Sept. 5, 2021, 5:38 p.m.