multi.impute: Function to impute quantitative datasets

Description Usage Arguments Value References Examples

View source: R/multi_impute.R

Description

This function creates an array made of slices of imputed dataset. Imputation methods can be chosen from c("pmm", "midastouch", "sample", "cart", "rf", "mean", "norm", "norm.nob", "norm.boot", "norm.predict").

Usage

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multi.impute(data, conditions, nb.imp = NULL, method, parallel = FALSE)

Arguments

data

Dataset to impute.

conditions

Vector with the condition values.

nb.imp

Number of imputed dataset to create.

method

Imputation method, choose from c("pmm", "midastouch", "sample", "cart", "rf", "mean", "norm", "norm.nob", "norm.boot", "norm.predict").

parallel

Use parallel computing?

Value

a numeric array of dim c(dim(data),nb.imp).

References

M. Chion, Ch. Carapito and F. Bertrand (2021). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. arxiv:2108.07086. https://arxiv.org/abs/2108.07086.

Examples

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library(mi4p)
data(datasim)
multi.impute(data = datasim[,-1], conditions = attr(datasim,"metadata")$Condition, method = "MLE")

mi4p documentation built on Aug. 19, 2021, 5:07 p.m.