See: Description
Class | Description |
---|---|
CompositeLogPrior |
This class implements a composite prior that can be used for DifferentiableStatisticalModel.
|
DoesNothingLogPrior |
This class defines a
LogPrior that does not penalize any parameter. |
LogPrior |
The abstract class for any log-prior used e.g.
|
SeparateGaussianLogPrior |
Class for a
LogPrior that defines a Gaussian prior on the parameters
of a set of DifferentiableStatisticalModel s
and a set of class parameters. |
SeparateLaplaceLogPrior |
Class for a
LogPrior that defines a Laplace prior on the parameters
of a set of DifferentiableStatisticalModel s
and a set of class parameters. |
SeparateLogPrior |
Abstract class for priors that penalize each parameter value independently
and have some variances (and possible means) as hyperparameters.
|
SimpleGaussianSumLogPrior |
This class implements a prior that is a product of Gaussian distributions
with mean 0 and equal variance for each parameter.
|