imputeMissing: imputeMissing: Impute missing phenotypes/covariates

Description Usage Arguments Value Examples

Description

Impute missing phenotype(s)/covariate, with selective censoring, from specific diallel categories based on posteriors.

Usage

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imputeMissing(dat, phenotype, covariate, postPred, postPred.cov, effectEst,
  SigmaEst, BlockEst, FixedEst, effectEst.cov, SigmaEst.cov, BlockEst.cov,
  toImpute, toCensor, colsToCopy, numImps, savedir, ...)

Arguments

dat

original data set

phenotype

the phenotype column name

covariate

the covariate column name

postPred

posterior predictive data for phenotype

postPred.cov

posterior predictive data for covariate

effectEst

posterior effect estimates for phenotype

SigmaEst

posterior sigma estimates for phenotype

BlockEst

posterior block estimates for phenotype

FixedEst

posterior fixed estimates for phenotype

effectEst.cov

posterior effect estimates for covariate

SigmaEst.cov

posterior sigma estimates for covariate

BlockEst.cov

posterior block estimates for covariate

toImpute

categories for imputation

toCensor

categories for censoring

colsToCopy

data columns from imputation frame to copy

numImps

number of timesteps to select from total (# imputed datasets to generate)

savedir

the directory the files are saved in

...

additional arguments

Value

generates (n=timestepLen) imputed datasets, returns vector of file names

Examples

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## not run

mauriziopaul/treatmentResponseDiallel documentation built on May 21, 2019, 1:37 p.m.