hai_winsorized_move_augment: Augment Function Winsorize Move

In healthyR.ai: The Machine Learning and AI Modeling Companion to 'healthyR'

Augment Function Winsorize Move

Description

Takes a numeric vector and will return a tibble with the winsorized values.

Usage

hai_winsorized_move_augment(.data, .value, .multiple, .names = "auto")

Arguments

.data	The data being passed that will be augmented by the function.
.value	This is passed rlang::enquo() to capture the vectors you want to augment.
.multiple	A positive number indicating how many times the the zero center mean absolute deviation should be multiplied by for the scaling parameter.
.names	The default is "auto"

Details

Takes a numeric vector and will return a winsorized vector of values that have been moved some multiple from the mean absolute deviation zero center of some vector. The intent of winsorization is to limit the effect of extreme values.

Value

An augmented tibble

Author(s)

Steven P. Sanderson II, MPH

See Also

https://en.wikipedia.org/wiki/Winsorizing

Other Augment Function: hai_fourier_augment(), hai_fourier_discrete_augment(), hai_hyperbolic_augment(), hai_polynomial_augment(), hai_scale_zero_one_augment(), hai_scale_zscore_augment(), hai_winsorized_truncate_augment()

Examples

suppressPackageStartupMessages(library(dplyr))

len_out <- 24
by_unit <- "month"
start_date <- as.Date("2021-01-01")

data_tbl <- tibble(
  date_col = seq.Date(from = start_date, length.out = len_out, by = by_unit),
  a = rnorm(len_out),
  b = runif(len_out)
)

hai_winsorized_move_augment(data_tbl, a, .multiple = 3)

healthyR.ai documentation built on April 3, 2023, 5:24 p.m.