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sdPrior  

Scale-Dependent Hyperpriors in Structured Additive Distributional Regression
View on CRAN: Click here


Download and install sdPrior package within the R console
Install from CRAN:
install.packages("sdPrior")

Install from Github:
library("remotes")
install_github("cran/sdPrior")

Install by package version:
library("remotes")
install_version("sdPrior", "1.0-0")



Attach the package and use:
library("sdPrior")
Maintained by
Nadja Klein
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-07-07
Latest Update: 2018-10-06
Description:
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) .
How to cite:
Nadja Klein (2015). sdPrior: Scale-Dependent Hyperpriors in Structured Additive Distributional Regression. R package version 1.0-0, https://cran.r-project.org/web/packages/sdPrior. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.2 (2015-07-07 17:47), 0.3 (2015-07-16 01:13), 0.5 (2018-05-29 09:37), 0.6 (2018-07-07 09:30)
Other packages that cited sdPrior R package
View sdPrior citation profile
Other R packages that sdPrior depends, imports, suggests or enhances
Complete documentation for sdPrior
Functions, R codes and Examples using the sdPrior R package
Some associated functions: DesignM . dapprox_unif . get_theta . get_theta_aunif . get_theta_ga . get_theta_gbp . get_theta_ig . get_theta_linear . hyperpar . hyperpar_mod . hyperparlin . mdbeta . mdf_aunif . mdf_ga . mdf_gbp . mdf_ig . mdf_sd . papprox_unif . rapprox_unif . zambia_graph . zambia_height92 . 
Some associated R codes: Full sdPrior package functions and examples
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