Other packages > Find by keyword >

makemyprior  

Intuitive Construction of Joint Priors for Variance Parameters
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("makemyprior", "1.2.2")



Attach the package and use:
library("makemyprior")
Maintained by
Ingeborg Hem
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-18
Latest Update: 2024-08-23
Description:
Tool for easy prior construction and visualization. It helps to formulates joint prior distributions for variance parameters in latent Gaussian models. The resulting prior is robust and can be created in an intuitive way. A graphical user interface (GUI) can be used to choose the joint prior, where the user can click through the model and select priors. An extensive guide is available in the GUI. The package allows for direct inference with the specified model and prior. Using a hierarchical variance decomposition, we formulate a joint variance prior that takes the whole model structure into account. In this way, existing knowledge can intuitively be incorporated at the level it applies to. Alternatively, one can use independent variance priors for each model components in the latent Gaussian model.
How to cite:
Ingeborg Hem (2021). makemyprior: Intuitive Construction of Joint Priors for Variance Parameters. R package version 1.2.2, https://cran.r-project.org/web/packages/makemyprior. Accessed 05 Jun. 2026.
Previous versions and publish date:
1.0.0 (2021-05-18 13:00), 1.0.1 (2022-02-21 14:30), 1.1.0 (2022-03-14 15:20), 1.2.0 (2024-03-06 14:10), 1.2.1 (2024-04-09 13:20)
Other packages that cited makemyprior R package
View makemyprior citation profile
Other R packages that makemyprior depends, imports, suggests or enhances
Complete documentation for makemyprior
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

msm  
Multi-State Markov and Hidden Markov Models in Continuous Time
Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal d ...
Download / Learn more Package Citations See dependency  
envirem  
Generation of ENVIREM Variables
Generation of bioclimatic rasters that are complementary to the typical 19 bioclim variables. ...
Download / Learn more Package Citations See dependency  
ibb  
R Wrapper for Istanbul Municipality Open Data Portal
Call wrappers for Istanbul Metropolitan Municipality's Open Data Portal (Turkish: Istanbul B ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
crossurr  
Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers
Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebau ...
Download / Learn more Package Citations See dependency  

27,268

R Packages

233,548

Dependencies

72,590

Author Associations

27,205

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA