log.integrated.gaussian.likelihood: Log Integrated Gaussian Likelihood
In Boom: Bayesian Object Oriented Modeling
log.integrated.gaussian.likelihood R Documentation
Log Integrated Gaussian Likelihood
Description
Compute the log of the integrated Gaussian likelihood,
where the model paramaters are integrated out with respect to a
normal-inverse gamma prior.
Usage
LogIntegratedGaussianLikelihood(suf, prior)
Arguments
suf
A GaussianSuf object describing the data.
prior
A NormalInverseGammaPrior describing the
prior distribution.
Value
Returns a scalar giving the log integrated likelihood.
Author(s)
Steven L. Scott steve.the.bayesian@gmail.com
Examples
prior <- NormalInverseGammaPrior(10, 2, sqrt(2), 1)
y <- c(7.8949, 9.17438, 8.38808, 5.52521)
suf <- GaussianSuf(y)
loglike <- LogIntegratedGaussianLikelihood(suf, prior)
# -9.73975
Boom documentation built on May 29, 2024, 5:08 a.m.
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| log.integrated.gaussian.likelihood | R Documentation |
Log Integrated Gaussian Likelihood
Description
Compute the log of the integrated Gaussian likelihood, where the model paramaters are integrated out with respect to a normal-inverse gamma prior.
Usage
LogIntegratedGaussianLikelihood(suf, prior)
Arguments
suf |
A |
prior |
A |
Value
Returns a scalar giving the log integrated likelihood.
Author(s)
Steven L. Scott steve.the.bayesian@gmail.com
Examples
prior <- NormalInverseGammaPrior(10, 2, sqrt(2), 1)
y <- c(7.8949, 9.17438, 8.38808, 5.52521)
suf <- GaussianSuf(y)
loglike <- LogIntegratedGaussianLikelihood(suf, prior)
# -9.73975
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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