stats-kurtosis: Kurtosis

kurtosisR Documentation

Kurtosis

Description

Generic function for computation of kurtosis. The methods defined in package timeDate are described here.

Usage

kurtosis(x, ...)

## Default S3 method:
kurtosis(x, na.rm = FALSE,
                  method = c("excess", "moment", "fisher"), ...)

## S3 method for class 'data.frame'
kurtosis(x, na.rm = FALSE,
                  method = c("excess", "moment", "fisher"), ...)

## S3 method for class 'POSIXct'
kurtosis(x, ...)

## S3 method for class 'POSIXlt'
kurtosis(x, ...)

Arguments

na.rm

a logical. Should missing values be removed?

method

a character string which specifies the method of computation. These are either "moment", "fisher", or "excess". If "excess" is selected, then the value of the kurtosis is computed by the "moment" method and a value of 3 will be subtracted. The "moment" method is based on the definitions of kurtosis for distributions; these forms should be used when resampling (bootstrap or jackknife). The "fisher" method correspond to the usual "unbiased" definition of sample variance, although in the case of kurtosis exact unbiasedness is not possible.

x

a numeric vector or object.

...

arguments to be passed.

Details

kurtosis is an S3 generic function. This page describes the methods defined in package dateTime.

If x is numeric the kurtosis is computed according to the description given for argument method. A logical vector is treated as a vector of 1's and 0's.

The data.frame method applies kurtosis recursively to each column. The POSIXlt method computes the kurtosis of the underlying numerical representation of the date/times. The method for POSIXct does the same after converting the argument to POSIXlt.

The default method returns NA, with a warning, if it can't handle argument x.

Value

a numeric value or vector with attribute "method" indicating the method.

See Also

skewness.

Examples

   
## mean -
## var -
   # Mean, Variance:
   r = rnorm(100)
   mean(r)
   var(r)
   
## kurtosis - 
   kurtosis(r)

   kurtosis(data.frame(r = r, r2 = r^2))


timeDate documentation built on Sept. 30, 2022, 5:07 p.m.