skewness {modeest}R Documentation

Skewness

Description

The skewness.default function from package fBasics is completed in order to implement Bickel's measure of skewness, based on the mode of the distribution considered.

Usage

skewness(x, 
         ...)
## Default S3 method:
skewness(x, 
         na.rm = FALSE, 
         method = c("moment", "fisher", "bickel"), 
         M = shorth(x), 
         ...)

Arguments

x numeric. Vector of observations.
na.rm logical. Should missing values be removed?
method character. Specifies the method of computation. These are either "moment", "fisher" or "bickel". The "moment" method is based on the definition of skewness for distributions; this form should be used when resampling (bootstrap or jackknife). The "fisher" method corresponds to the usual "unbiased" definition of sample variance, although in the case of skewness exact unbiasedness is not possible.
M numeric. (An estimate of) the mode of the observations x. Default value is shorth(x).
... arguments to be passed.

Value

skewness returns a numeric value. An attribute which reports the used method is added.

Author(s)

Diethelm Wuertz and other authors for the original skewness function from package fBasics;
Paul Poncet paulponcet@yahoo.fr for the slight modification introduced.

References

See Also

015A-BasicStatistics from package fBasics; mlv for general mode estimation; shorth for the shorth estimate of the mode;

Examples

## Skewness = 0
x <- rnorm(1000)
skewness(x, method = "bickel", M = shorth(x))

## Skewness > 0 (left skewed case)
x <- rbeta(1000, 2, 5)
skewness(x, method = "bickel", M = betaMode(2, 5))

## Skewness < 0 (right skewed case)
x <- rbeta(1000, 7, 2)
skewness(x, method = "bickel", M = hsm(x, bw = 1/3))

[Package modeest version 1.06 Index]