Description Usage Arguments Value Examples
Impute missing phenotype(s)/covariate, with selective censoring, from specific diallel categories based on posteriors.
1 2 3 | imputeMissing(dat, phenotype, covariate, postPred, postPred.cov, effectEst,
SigmaEst, BlockEst, FixedEst, effectEst.cov, SigmaEst.cov, BlockEst.cov,
toImpute, toCensor, colsToCopy, numImps, savedir, ...)
|
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 |
generates (n=timestepLen) imputed datasets, returns vector of file names
1 | ## not run
|
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