modeest (version 1.06)

skewness: 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, 
         ...)
## S3 method for class 'default':
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

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.

References

• Bickel D.R. (2002). Robust estimators of the mode and skewness of continuous data.Computational Statistics and Data Analysis,39:153-163.
• Bickel D.R. et Fr�hwirth R. (2006). On a Fast, Robust Estimator of the Mode: Comparisons to Other Robust Estimators with Applications.Computational Statistics and Data Analysis,50(12):3500-3530.

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))