Boom: normal.inverse.gamma.prior – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

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

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.
`...`	blah

Author(s)

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

References

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

Boom

Bayesian Object Oriented Modeling

v0.9.7

LGPL-2.1 | file LICENSE

Authors

Steven L. Scott is the sole author and creator of the BOOM project. Some code in the BOOM libraries has been modified from other open source projects. These include Cephes (obtained from Netlib, written by Stephen L. Moshier), NEWUOA (M.J.D Powell, obtained from Powell's web site), and a modified version of the R math libraries (R core development team). Original copyright notices have been maintained in all source files. In these cases, copyright claimed by Steven L. Scott is limited to modifications made to the original code. Google claims copyright for code written while Steven L. Scott was employed at Google from 2008 - 2018, but BOOM is not an officially supported Google project.

Initial release

2021-02-15