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Boom

ar1.coefficient.prior

Normal prior for an AR1 coefficient

Description

A (possibly truncated) Gaussian prior on the autoregression coefficient in an AR1 model.

Usage

Ar1CoefficientPrior(mu = 0, sigma = 1, force.stationary = TRUE,
    force.positive = FALSE, initial.value = mu)

Arguments

mu

The mean of the prior distribution.
sigma

The standard deviation of the prior distribution.
force.stationary

Logical. If TRUE then the prior support for the AR1 coefficient will be truncated to (-1, 1).
force.positive

Logical. If TRUE then the prior for the AR1 coefficient will be truncated so that zero support is given to values less than zero.
initial.value

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

Details

The Ar1CoefficientPrior() syntax is preferred, as it more closely matches R's syntax for other constructors.

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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