imputeData: Missing data imputation via the 'mix' package

Description Usage Arguments Value References See Also Examples

View source: R/impute.R

Description

Imputes missing data using the mix package.

Usage

1
imputeData(data, categorical = NULL, seed = NULL, verbose = interactive())

Arguments

data

A numeric vector, matrix, or data frame of observations containing missing values. Categorical variables are allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables.

categorical

A logical vectors whose ith entry is TRUE if the ith variable or column of data is to be interpreted as categorical and FALSE otherwise. The default is to assume that a variable is to be interpreted as categorical only if it is a factor.

seed

A seed for the function rngseed that is used to initialize the random number generator in mix. By default, a seed is chosen uniformly in the interval (.Machine$integer.max/1024, .Machine$integer.max).

verbose

A logical, if TRUE reports info about iterations of the algorithm.

Value

A dataset of the same dimensions as data with missing values filled in.

References

Schafer J. L. (1997). Analysis of Imcomplete Multivariate Data, Chapman and Hall.

See Also

imputePairs

Examples

1
2
3
4
5
6
7
8
# Note that package 'mix' must be installed
data(stlouis, package = "mix")
 
# impute the continuos variables in the stlouis data
stlimp <- imputeData(stlouis[,-(1:3)])

# plot imputed values
imputePairs(stlouis[,-(1:3)], stlimp)

Example output

Package 'mclust' version 5.3
Type 'citation("mclust")' for citing this R package in publications.

mclust documentation built on May 29, 2017, 5:36 p.m.