pmice: Impute missing data in parallel
In b-rodrigues/pmice: Impute Missing Data in Parallel
Description
Impute missing data in parallel
Usage
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pmice(data, m = 5, method = vector("character", length = ncol(data)),
predictorMatrix = (1 - diag(1, ncol(data))), where = is.na(data),
visitSequence = NULL, form = vector("character", length = ncol(data)),
post = vector("character", length = ncol(data)), defaultMethod = c("pmm",
"logreg", "polyreg", "polr"), maxit = 5, diagnostics = TRUE,
printFlag = FALSE, seed = NULL, imputationMethod = NULL,
defaultImputationMethod = NULL, data.init = NULL, ...)
b-rodrigues/pmice documentation built on May 12, 2019, 6:26 p.m.
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Description
Impute missing data in parallel
Usage
1 2 3 4 5 6 7 | pmice(data, m = 5, method = vector("character", length = ncol(data)),
predictorMatrix = (1 - diag(1, ncol(data))), where = is.na(data),
visitSequence = NULL, form = vector("character", length = ncol(data)),
post = vector("character", length = ncol(data)), defaultMethod = c("pmm",
"logreg", "polyreg", "polr"), maxit = 5, diagnostics = TRUE,
printFlag = FALSE, seed = NULL, imputationMethod = NULL,
defaultImputationMethod = NULL, data.init = NULL, ...)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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