dstudent: Non-standard Student's t distribution
In JimmyClowes/rethinking: Statistical Rethinking book package

Description Usage Arguments Details Author(s) Examples

Functions for computing density and producing random samples from a non-standardized Student's t distribution.

1 2	dstudent( x, nu = 2, mu = 0, sigma = 1, log = FALSE ) rstudent( n, nu = 2, mu = 0, sigma = 1 )

`x`	Values to compute densities of
`nu`	Degrees of freedom (tail shape)
`mu`	Location of distribution (mean)
`sigma`	Scale of distribution
`log`	If `TRUE`, returns log-density instead of density
`n`	Number of random observations to sample

These functions provide density and random number calculations for Student's t distribution, translated and scaled by mean mu and scale sigma. Note that sigma is not the distribution's standard deviation, unless nu is very large.

Richard McElreath

## Not run: 
library(rethinking)
data(WaffleDivorce)
d <- WaffleDivorce
d$A <- scale( d$MedianAgeMarriage )
d$D <- scale( d$Divorce )
d$M <- scale( d$Marriage )

m5.3b <- quap(
    alist(
        D ~ dstudent( 2 , mu , sigma ) ,
        mu <- a + bM*M + bA*A ,
        a ~ dnorm( 0 , 0.2 ) ,
        bM ~ dnorm( 0 , 0.5 ) ,
        bA ~ dnorm( 0 , 0.5 ) ,
        sigma ~ dexp( 1 )
    ) , data = d )

## End(Not run)