na_pca: Dimmensionality reduction to visualize missing data

In twolodzko/misster: Simple tools for dealing with missing values

Description

Dimmensionality reduction to visualize missing data

Usage

na_pca(data, formula, ..., plot = TRUE)

na_tsne(data, formula, ..., plot = TRUE)

Arguments

data	a data.frame.
formula	an object of class "formula": a symbolic description of the model to be fitted.
...	further arguments passed to other methods.
plot	if TRUE prints plots of the first two components extracted using PCA or t-SNE with highlited missing values.

See Also

princomp, Rtsne

Examples

set.seed(1234)

dat <- mtcars
dat$disp[sample.int(nrow(dat), 10)] <- NA

na_pca(dat, disp ~ mpg + cyl + disp)
na_tsne(dat, disp ~ ., perplexity = 10)

twolodzko/misster documentation built on May 24, 2019, 2:54 p.m.