## File: stats-kurtosis.Rd

package info (click to toggle)
r-cran-timedate 3012.100-2
 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990 \name{kurtosis} \alias{kurtosis} \alias{kurtosis.default} \alias{kurtosis.data.frame} \alias{kurtosis.POSIXct} \alias{kurtosis.POSIXlt} \title{Kurtosis} \description{ Functions to compute kurtosis. } \usage{ kurtosis(x, \dots) \method{kurtosis}{default}(x, na.rm = FALSE, method = c("excess", "moment", "fisher"), \dots) \method{kurtosis}{data.frame}(x, \dots) \method{kurtosis}{POSIXct}(x, \dots) \method{kurtosis}{POSIXlt}(x, \dots) } \arguments{ \item{na.rm}{ a logical. Should missing values be removed? } \item{method}{ a character string which specifies the method of computation. These are either \code{"moment"}, \code{"fisher"}, or \code{"excess"}. If \code{"excess"} is selected, then the value of the kurtosis is computed by the \code{"moment"} method and a value of 3 will be subtracted. The \code{"moment"} method is based on the definitions of kurtosis for distributions; these forms should be used when resampling (bootstrap or jackknife). The \code{"fisher"} method correspond to the usual "unbiased" definition of sample variance, although in the case of kurtosis exact unbiasedness is not possible. } \item{x}{ a numeric vector or object. } \item{\dots}{ arguments to be passed. } } \value{ \code{kurtosis} returns the value of the statistics, a numeric value. An attribute which reports the used method is added. } \seealso{ \code{link{skewness}}. } \examples{ ## mean - ## var - # Mean, Variance: r = rnorm(100) mean(r) var(r) ## kurtosis - kurtosis(r) } \keyword{univar}