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R
Boom

lognormal.prior

Lognormal Prior Distribution

Description

Specifies a lognormal prior distribution.

Usage

LognormalPrior(mu = 0.0, sigma = 1.0, initial.value = NULL)

Arguments

mu

mean of the corresponding normal distribution.
sigma

standard deviation of the corresponding normal distribution. WARNING: If something looks strange in your program, look out for SD != Variance errors.
initial.value

Initial value of the variable to be modeled (e.g. in an MCMC algorithm). If NULL then the prior mean will be used.

Details

A lognormal distribution, where log(y) ~ N(mu, sigma). The mean of this distribution is exp(mu + 0.5 * sigma^2), so don't only focus on the mean parameter here.

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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