mi: mipply – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

mipply

Apply a Function to a Object of Class mi

Description

This function is a wrapper around sapply that is invoked on the data slot of an object of mi-class and / or on an object of missing_data.frame-class after being coerced to a data.frame

Usage

mipply(X, FUN, ..., simplify = TRUE, USE.NAMES = TRUE, 
       columnwise = TRUE, to.matrix = FALSE)

Arguments

`X`	Object of `mi-class`, `missing_data.frame-class`, `missing_variable-class`, `mi_list-class`, or `mdf_list-class`
`FUN`	Function to call
`...`	Further arguments passed to `FUN`, currently broken
`simplify`	If `TRUE`, coerces result to a vector or matrix if possible
`USE.NAMES`	ignored but included for compatibility with `sapply`
`columnwise`	logical indicating whether to invoke `FUN` on the columns of a `missing_data.frame` after coercing it to a `data.frame` or a `matrix` or to invoke `FUN` on the “whole” `data.frame` or `matrix`
`to.matrix`	Logical indicating whether to coerce each `missing_data.frame` to a numeric `matrix` or to a `data.frame`. The default is `FALSE`, in which case the `data.frame` will include `factor`s if any of the `missing_variable`s inherit from `categorical-class`

Details

The columnwise and to.matrix arguments are the only additions to the argument list in sapply, see the Examples section for an illustration of their use. Note that functions such as mean only accept numeric inputs, which can produce errors or warnings when to.matrix = FALSE.

Value

A list, vector, or matrix depending on the arguments

Author(s)

Ben Goodrich and Jonathan Kropko, for this version, based on earlier versions written by Yu-Sung Su, Masanao Yajima, Maria Grazia Pittau, Jennifer Hill, and Andrew Gelman.

Examples

if(!exists("imputations", env = .GlobalEnv)) {
  imputations <- mi:::imputations # cached from example("mi-package")
}
round(mipply(imputations, mean, to.matrix = TRUE), 3)
mipply(imputations, summary, columnwise = FALSE)

mi

Missing Data Imputation and Model Checking

v1.0

GPL (>= 2)

Authors

Andrew Gelman [ctb], Jennifer Hill [ctb], Yu-Sung Su [aut], Masanao Yajima [ctb], Maria Pittau [ctb], Ben Goodrich [cre, aut], Yajuan Si [ctb], Jon Kropko [aut]

Initial release

2015-04-16