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 DifferentiableStatisticalModels
and a set of class parameters. |
| SeparateLaplaceLogPrior |
Class for a
LogPrior that defines a Laplace prior on the parameters
of a set of DifferentiableStatisticalModels
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.
|