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

Description Usage Arguments Value Author(s) See Also Examples

Description

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

Usage

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

Arguments

tab.l

A numeric matrix of lower bounds for missing values.

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 in the confidence intervals defined thanks to tab.l and tab.u.

Author(s)

Quentin Giai Gianetto <[email protected]>

See Also

estim.mix

Examples

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#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$tab.lower,born$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);

#Histogram of probabilities to be MCAR associated to generated MNAR values
hist(

proba[which(is.na(res.sim$dat.obs[,1]))[

!which(is.na(res.sim$dat.obs[,1]))%in%res.sim$list.MCAR[[1]]],1

],

freq=FALSE,main="Estimated probabilities to be MCAR for known MNAR values",xlab="",col=4
);

imp4p documentation built on Aug. 10, 2018, 5:03 p.m.