normal.inverse.gamma.prior: Normal inverse gamma prior

normal.inverse.gamma.priorR Documentation

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 \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.

...

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Author(s)

Steven L. Scott steve.the.bayesian@gmail.com

References

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


Boom documentation built on May 29, 2024, 5:08 a.m.