`[dpr]mvss`

: mutivariate subgaussian stable distributions

The goal of `mvpd`

is to use product distribution theory
to allow the numerical calculations of specific scale mixtures of the
multivariate normal distribution. The multivariate subgaussian stable
distribution is the product of the square root of a univariate positive
stable distribution and the multivariate normal distribution (see Nolan
(2013)).

Generate 1000 draws from a random bivariate subgaussian stable distribution with alpha=1.71 and plot.

```
library(mvpd)
set.seed(10)
## basic example code
<- rmvss(n=1e3, alpha=1.71, Q=matrix(c(10,7.5,7.5,10),2))
biv head(biv)
#> [,1] [,2]
#> [1,] -0.2260798 -0.6168492
#> [2,] -6.1460819 -4.5603538
#> [3,] 1.4592466 1.6213040
#> [4,] -4.4159078 -2.9252448
#> [5,] -6.7106973 -3.8158068
#> [6,] 5.9107788 5.1332625
plot(biv); abline(h=0,v=0)
```