winsorize: Winsorize transformation

In spatialEco: Spatial Analysis and Modelling Utilities

Winsorize transformation

Description

Removes extreme outliers using a winsorization transformation

Usage

winsorize(
  x,
  min.value = NULL,
  max.value = NULL,
  p = c(0.05, 0.95),
  na.rm = FALSE
)

Arguments

x	A numeric vector
min.value	A fixed lower bounds, all values lower than this will be replaced by this value. The default is set to the 5th-quantile of x.
max.value	A fixed upper bounds, all values higher than this will be replaced by this value. The default is set to the 95th-quantile of x.
p	A numeric vector of 2 representing the probabilities used in the quantile function.
na.rm	(FALSE/TRUE) should NAs be omitted?

Details

Winsorization is the transformation of a distribution by limiting extreme values to reduce the effect of spurious outliers. This is done by shrinking outlying observations to the border of the main part of the distribution.

Value

A transformed vector the same length as x, unless na.rm is TRUE, then x is length minus number of NA's

Author(s)

Jeffrey S. Evans <[e-mail]>

References

Dixon, W.J. (1960) Simplified Estimation from Censored Normal Samples. Annals of Mathematical Statistics. 31(2):385-391

Examples

set.seed(1234)     
x <- rnorm(100)     
x[1] <- x[1] * 10  
winsorize(x)       

plot(x, type="l", main="Winsorization transformation")
  lines(winsorize(x), col="red", lwd=2)
    legend("bottomright", legend=c("Original distribution","With outliers removed"),
        lty=c(1,1), col=c("black","red"))

# Behavior with NA value(s)
x[4] <- NA
winsorize(x)             # returns x with original NA's 
winsorize(x, na.rm=TRUE) # removes NA's 

spatialEco documentation built on Nov. 18, 2023, 1:13 a.m.