normal.inverse.gamma.prior: Normal inverse gamma prior
Description
The NormalInverseGammaPrior is the conjugate prior for the
mean and variance of the scalar normal distribution. The model says
that
$$\frac{1}{\sigma^2} \sim Gamma(df / 2, ss/2) \mu|\sigma \sim
N(\mu_0, \sigma^2/\kappa)$$
Usage
NormalInverseGammaPrior(mu.guess, mu.guess.weight = .01, sigma.guess, sigma.guess.weight = 1, ...)
Arguments
mu.guess
The mean of the prior distribution. This is
$\mu0$ in the description above.
mu.guess.weight
The number of observations worth of weight
assigned to mu.guess. This is $\kappa$ in the
description above.
sigma.guess
A prior estimate at the value of sigma.
This is $\sqrt{ss/df}$.
sigma.guess.weight
The number of observations worth of weight
assigned to sigma.guess. This is $df$.
References
Gelman, Carlin, Stern, Rubin (2003), "Bayesian Data Analysis", Chapman
and Hall.