These are density, distribution function, quantile function and random generation
for the Student-t distribution with location `mu`

, scale `sigma`

,
and degrees of freedom `df`

. Base R gives you the so-called "standard" Student-t
distribution, with just the varying degrees of freedom. This generalizes that standard
Student-t to the three-parameter version.

dst(x, df, mu, sigma) pst(q, df, mu, sigma) qst(p, df, mu, sigma) rst(n, df, mu, sigma)

x, q | a vector of quantiles |
---|---|

df | a vector of degrees of freedom |

mu | a vector for the location value |

sigma | a vector of scale values |

p | Vector of probabilities. |

n | Number of samples to draw from the distribution. |

`dst()`

returns the density. `pst()`

returns the distribution function. `qst()`

returns the quantile function.
`rst()`

returns random numbers.

This is a simple hack taken from Wikipedia. It's an itch I've been wanting to scratch for a while. I can probably generalize this outward to allow the tail and log stuff, but I wrote this mostly for the random number generation. Right now, I haven't written this to account for the fact that sigma should be non-negative, but that's on the user to know that (for now).