na_random: Replace missing data with random values
In twolodzko/misster: Simple tools for dealing with missing values

Description Usage Arguments Details See Also

View source: R/random.R

Replace missing data with random values

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na_random(x, replace = TRUE)

na_density(x, bw = bw.nrd0(na.omit(x)), adjust = 1, preserve_var = TRUE)

`x`	a vector.
`replace`	should sampling be with replacement? `TRUE` by default.
`bw`	the smoothing bandwidth to be used.
`adjust`	the bandwidth used is actually `adjust*bw`.
`preserve_var`	if `TRUE` random generation algorithm preserves mean and variance of the original sample.

na_random replaces missing data with non-missing values drawn from the data with, or without replacement. na_density replaces missing values with draws from Gaussian kernel density estimated on the non-missing data. The preserve_var argument for na_density if set to TRUE (default), leads to producing samples that have the same variance as the original data.

sample, density

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