Takes a numeric vector and will return a vector of winsorized values.
Arguments
- .x
A numeric vector
- .multiple
A positive number indicating how many times the the zero center mean absolute deviation should be multiplied by for the scaling parameter.
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.
See also
https://en.wikipedia.org/wiki/Winsorizing
This function can be used on it's own. It is also the basis for the function
hai_winsorized_move_augment().
Other Vector Function:
hai_fourier_discrete_vec(),
hai_fourier_vec(),
hai_hyperbolic_vec(),
hai_kurtosis_vec(),
hai_scale_zero_one_vec(),
hai_scale_zscore_vec(),
hai_skewness_vec(),
hai_winsorized_truncate_vec()
Examples
suppressPackageStartupMessages(library(dplyr))
len_out <- 25
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)
)
vec_1 <- hai_winsorized_move_vec(data_tbl$a, .multiple = 1)
plot(data_tbl$a)
lines(data_tbl$a)
lines(vec_1, col = "blue")
