dst: Student t distribution with location mu, scale sigma, and nu...

In kuperov/acfunc: Extra distributions for Bayesian analysis

Description

The pdf of the Student t distribution is given in Gelman et al (2014, p.578):

t(x | μ, σ, ν) = \frac{γ≤ft(\frac{ν+1}{2}\right)}{γ(\frac{ν}{2})√{νπ}σ}≤ft(1 + \frac{1}{ν}≤ft(\frac{x-μ}{σ}\right)^2\right)^{-\frac{ν+1}{2}}

Usage

dst(x, df, location = 0, scale = 1, log = FALSE)

rst(n, df, location = 0, scale = 1)

pst(q, df, location = 0, scale = 1)

Arguments

x	vector of quantiles
df	degrees of freedom
location	mu parameter
scale	parameter (can be written sigma or sigma^2; this is 'sigma^2' in the above expression)
log	return logarithm of value if true
n	number of random deviates to draw
q	vector of quantiles

Value

'dst' gives the density and 'rst' generates random deviates.

References

Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2014). Bayesian data analysis (3E). Boca Raton, FL, USA: Chapman & Hall/CRC.

kuperov/acfunc documentation built on May 6, 2019, 10:50 p.m.