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R
Boom

normal.prior

Normal (scalar Gaussian) prior distribution

Description

Specifies a scalar Gaussian prior distribution.

Usage

NormalPrior(mu, sigma, initial.value = mu, fixed = FALSE)

Arguments

mu

The mean of the prior distribution.
sigma

The standard deviation of the prior distribution.
initial.value

The initial value of the parameter being modeled in the MCMC algorithm.
fixed

Should the deviate modeled by this distribution be fixed at its initial value? (Used for debugging in some code. Not universally respected.)

Author(s)

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

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