This function draws from a Wishart and inverted Wishart distribution.

## Usage

rwishart(nu, V)

## Arguments

nu

A numeric, the degrees of freedom. Must be at least the number of dimensions.

V

A matrix, the scale matrix.

## Value

A list, the draws from the Wishart (W), inverted Wishart (IW), and corresponding Choleski decomposition (C and CI).

## Details

The Wishart distribution is a generalization to multiple dimensions of the gamma distributions and draws from the space of covariance matrices. Its expectation is nu*V and its variance increases both in nu and in the values of V. The Wishart distribution is the conjugate prior to the precision matrix of a multivariate normal distribution and proper if nu is greater than the number of dimensions.

## Examples

rwishart(nu = 2, V = diag(2))
#> $W #> [,1] [,2] #> [1,] 1.277530 -2.393022 #> [2,] -2.393022 4.494557 #> #>$IW
#>          [,1]      [,2]
#> [1,] 292.2886 155.62223
#> [2,] 155.6222  83.07991
#>
#> $C #> [,1] [,2] #> [1,] 1.130279 -2.1171964 #> [2,] 0.000000 0.1097115 #> #>$CI
#>           [,1]      [,2]
#> [1,] 0.8847376 17.073542
#> [2,] 0.0000000  9.114818
#>