timeDate (version 4032.109)

kurtosis: Kurtosis

Description

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

Usage

kurtosis(x, ...)

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

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

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

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

Value

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

Arguments

x

a numeric vector or object.

na.rm

a logical. Should missing values be removed?

method

a character string, the method of computation, see section ‘Details’.

...

arguments to be passed.

Details

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

Argument "method" can be one of "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 and this method 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.

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.

See Also

skewness

Examples

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

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

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