naive_fill_NA: 'naive_fill_NA' function for the imputations purpose.

Description Usage Arguments Value Methods (by class) Note See Also Examples

View source: R/naive_fill_NA.R

Description

Regular imputations to fill the missing data. Non missing independent variables are used to approximate a missing observations for a dependent variable. For numeric columns with any missing data a simple bayesian mean will be used. Next all numeric variables will be utilized to impute character/factoer variables by Linear Discriminant Analysis.

Usage

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naive_fill_NA(x)

## S3 method for class 'data.frame'
naive_fill_NA(x)

## S3 method for class 'matrix'
naive_fill_NA(x)

Arguments

x

a numeric matrix or data.frame/data.table (factor/character/numeric/logical) - variables

Value

load imputations in a similar to the input type

Methods (by class)

Note

this is a very simple and fast solution but not recommended, for more complex solutions check the vignette

See Also

fill_NA fill_NA_N VIF

Examples

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## Not run: 
library(naive_fill_NAast)
data(air_miss)
naive_fill_NA(air_miss)

## End(Not run)

miceFast documentation built on July 11, 2021, 1:06 a.m.