# stats-kurtosis: Kurtosis In timeDate: Rmetrics - Chronological and Calendar Objects

 kurtosis R 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

 `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`.

### Value

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

`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 Jan. 7, 2023, 5:30 p.m.