marginalLikelihood_bySufficientStatistics.LinearGaussianGaussian {bbricks} | R Documentation |
Generate the marginal likelihood of the following model structure:
x \sim Gaussian(A z + b, Sigma)
z \sim Gaussian(m,S)
Where Sigma is known. A is a dimx x dimz matrix, x is a dimx x 1 random vector, z is a dimz x 1 random vector, b is a dimm x 1 vector. Gaussian() is the Gaussian distribution. See ?dGaussian
for the definition of Gaussian distribution.
The model structure and prior parameters are stored in a "LinearGaussianGaussian" object.
Marginal likelihood = p(x|m,S,Sigma)
## S3 method for class 'LinearGaussianGaussian' marginalLikelihood_bySufficientStatistics(obj, ss, LOG = TRUE, ...)
obj |
A "LinearGaussianGaussian" object. |
ss |
Sufficient statistics of x. In Gaussian-Gaussian case the sufficient statistic of sample x is a object of type "ssGaussianMean", it can be generated by the function sufficientStatistics(). |
LOG |
Return the log density if set to "TRUE". |
... |
Additional arguments to be passed to other inherited types. |
numeric, the marginal likelihood.
LinearGaussianGaussian
, marginalLikelihood.LinearGaussianGaussian