MvnGivenSigmaMatrixPrior: Conditional Multivaraite Normal Prior Given Variance
In Boom: Bayesian Object Oriented Modeling
View source: R/prior_specification.R
MvnGivenSigmaMatrixPrior R Documentation
Conditional Multivaraite Normal Prior Given Variance
Description
A multivaraite normal prior distribution, typically used as
the prior distribution for the mean of multivaraite normal data. The
variance of this distribution is proportional to another parameter
"Sigma" that exists elsewhere. Usually "Sigma" is the variance of the
data.
This distribution is the "normal" part of a "normal-inverse Wishart"
distribution.
Usage
MvnGivenSigmaMatrixPrior(mean, sample.size)
Arguments
mean
A vector giving the mean of the prior distribution.
sample.size
A positive scalar. The variance of the
distribution is Sigma / sample.size.
Author(s)
Steven L. Scott steve.the.bayesian@gmail.com
References
Gelman, Carlin, Stern, Rubin (2003), "Bayesian Data Analysis", Chapman
and Hall.
Boom documentation built on May 29, 2024, 5:08 a.m.
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View source: R/prior_specification.R
| MvnGivenSigmaMatrixPrior | R Documentation |
Conditional Multivaraite Normal Prior Given Variance
Description
A multivaraite normal prior distribution, typically used as the prior distribution for the mean of multivaraite normal data. The variance of this distribution is proportional to another parameter "Sigma" that exists elsewhere. Usually "Sigma" is the variance of the data.
This distribution is the "normal" part of a "normal-inverse Wishart" distribution.
Usage
MvnGivenSigmaMatrixPrior(mean, sample.size)
Arguments
mean |
A vector giving the mean of the prior distribution. |
sample.size |
A positive scalar. The variance of the
distribution is |
Author(s)
Steven L. Scott steve.the.bayesian@gmail.com
References
Gelman, Carlin, Stern, Rubin (2003), "Bayesian Data Analysis", Chapman and Hall.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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