Trim a Vector

Clean data by means of trimming, i.e., by omitting outlying observations.

Usage

trim(x, trim = 0.1, na.rm = FALSE)

Arguments

x: a numeric vector to be trimmed.
trim: the fraction (0 to 0.5) of observations to be trimmed from each end of x. Values of trim outside that range (and < 1) are taken as the nearest endpoint. If trim is set to a value >1 it's interpreted as the number of elements to be cut off at each tail of x.
na.rm: a logical value indicating whether NA values should be stripped before the computation proceeds.

Value

the trimmed vector x. The indices of the trimmed values will be attached as attribute named "trim".

Details

A symmetrically trimmed vector x with a fraction of trim observations (resp. the given number) deleted from each end will be returned. If trim is set to a value \(\ge 0.5\) or to an integer value \(\ge n/2\) then the result will be NA. The same applies if x contains NAs and na.rm is FALSE.

Note

This function is basically an excerpt from the base function mean(), which allows the vector x to be trimmed before calculating the mean.

Examples


## generate data
set.seed(1234)     # for reproducibility
x <- rnorm(10)     # standard normal
x[1] <- x[1] * 10  # introduce outlier

## Trim data
x
#>  [1] -12.0706575   0.2774292   1.0844412  -2.3456977   0.4291247   0.5060559
#>  [7]  -0.5747400  -0.5466319  -0.5644520  -0.8900378
trim(x, trim=0.1)
#> [1]  0.2774292 -2.3456977  0.4291247  0.5060559 -0.5747400 -0.5466319 -0.5644520
#> [8] -0.8900378
#> attr(,"trim")
#> [1] 1 3

## Trim fixed number, say cut the 3 extreme elements from each end
trim(x, trim=3)
#> [1]  0.2774292 -0.5747400 -0.5466319 -0.5644520
#> attr(,"trim")
#> [1]  1  4 10  5  6  3

## check function
s <- sample(10:20)
s.tr <- trim(s, trim = 2)
setequal(c(s[attr(s.tr, "trim")], s.tr), s)
#> [1] TRUE