normal.inverse.gamma.prior {Boom}R 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

1/σ^2 ~ Gamma(df/2, ss/2) μ | σ ~ N(μ0, σ^2/κ)

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 μ0 in the description above.

mu.guess.weight

The number of observations worth of weight assigned to mu.guess. This is κ in the description above.

sigma.guess

A prior estimate at the value of sigma. This is √{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.


[Package Boom version 0.9.1 Index]