normal.inverse.wishart.prior {Boom} | R Documentation |
Normal inverse Wishart prior
Description
The NormalInverseWishartPrior is the conjugate prior for the mean and variance of the multivariate normal distribution. The model says that
The distribution is parameterized by
S
,
the inverse of the sum of squares matrix, and the scalar
degrees of freedom parameter nu
.
The distribution is improper if .
Usage
NormalInverseWishartPrior(mean.guess,
mean.guess.weight = .01,
variance.guess,
variance.guess.weight = nrow(variance.guess) + 1)
Arguments
mean.guess |
The mean of the prior distribution. This is
|
mean.guess.weight |
The number of observations worth of weight
assigned to |
variance.guess |
A prior estimate at the value of |
variance.guess.weight |
The number of observations worth of weight
assigned to |
Author(s)
Steven L. Scott steve.the.bayesian@gmail.com
References
Gelman, Carlin, Stern, Rubin (2003), "Bayesian Data Analysis", Chapman and Hall.