sdPrior: Scale-Dependent Hyperpriors in Structured Additive Distributional Regression
Version 0.5

Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) .

Getting started

Package details

AuthorNadja Klein [aut, cre], Thomas Kneib [aut]
Date of publication2018-05-29 07:37:18 UTC
MaintainerNadja Klein <[email protected]>
Package repositoryView on CRAN
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sdPrior documentation built on May 29, 2018, 9:04 a.m.