R: Normal inverse gamma prior

normal.inverse.gamma.prior {Boom}

R Documentation

Normal inverse gamma prior

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)

NormalInverseGammaPrior(mu.guess, mu.guess.weight = .01,
       sigma.guess, sigma.guess.weight = 1, ...)

`mu.guess`	The mean of the prior distribution. This is `\mu_0` 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`.
`...`	blah

Gelman, Carlin, Stern, Rubin (2003), "Bayesian Data Analysis", Chapman and Hall.

[Package Boom version 0.9.15 Index]