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markov.prior

Prior for a Markov chain


Description

The conjugate prior distribution for the parameters of a homogeneous Markov chain. The rows in the transition probability matrix modeled with independent Dirichlet priors. The distribution of the initial state is modeled with its own independent Dirichlet prior.

Usage

MarkovPrior(prior.transition.counts = NULL,
            prior.initial.state.counts = NULL,
            state.space.size = NULL,
            uniform.prior.value = 1)

Arguments

prior.transition.counts

A matrix of the same dimension as the transition probability matrix being modeled. Entry (i, j) represents the "prior count" of transitions from state i to state j.

prior.initial.state.counts

A vector of positive numbers representing prior counts of initial states.

state.space.size

If both prior.transition.counts and prior.initial.state.counts are missing, then they will be filled with an object of dimension state.space.size where all entries are set to uniform.prior.value.

uniform.prior.value

The default value to use for entries of prior.transition.counts and prior.initial.state.counts, when they are not supplied by the user.

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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