pi_mcar_logit: Estimating the proportion of MCAR values in a sample using a...
In imp4p: Imputation for Proteomics

Description Usage Arguments Value Author(s) See Also Examples

This function allows estimating the proportion of MCAR values in a sample using a logit model.

1	pi.mcar.logit(tab,conditions)

`tab`	A data matrix containing numeric and missing values. Each column of this matrix is assumed to correspond to an experimental sample, and each row to an identified peptide.
`conditions`	A vector of factors indicating the biological condition to which each column (experimental sample) belongs.

A list composed of:

`pi.mcar`	The estimated proportion of MCAR values.
`coef1`	The estimated intercept of each logit model estimated in a sample.
`coef2`	The estimated coefficient of each logit model estimated in a sample.

Quentin Giai Gianetto <quentin2g@yahoo.fr>

estim.mix

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

#Proportion of MCAR values in each sample
pi.mcar.logit(tab=res.sim$dat.obs,conditions=res.sim$conditions)