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revdbayes  

Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("revdbayes", "1.5.5")



Attach the package and use:
library("revdbayes")
Maintained by
Paul J. Northrop
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-11-23
Latest Update: 2023-01-05
Description:
Provides functions for the Bayesian analysis of extreme value models. The 'rust' package is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package , which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. In addition, there are functions for making inferences about the extremal index, using the models for threshold inter-exceedance times of Suveges and Davison (2010) and Holesovsky and Fusek (2020) . Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
How to cite:
Paul J. Northrop (2016). revdbayes: Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis. R package version 1.5.5, https://cran.r-project.org/web/packages/revdbayes. Accessed 21 Dec. 2024.
Previous versions and publish date:
1.0.0 (2016-11-23 14:09), 1.1.0 (2017-03-14 15:13), 1.2.0 (2017-07-14 22:10), 1.2.1 (2017-08-21 15:46), 1.3.1 (2017-11-02 01:57), 1.3.2 (2018-02-13 00:15), 1.3.3 (2019-03-08 20:00), 1.3.4 (2019-06-22 00:00), 1.3.5 (2019-11-04 18:00), 1.3.6 (2019-12-02 11:30), 1.3.7 (2020-06-26 20:20), 1.3.8 (2020-08-31 09:30), 1.3.9 (2020-09-12 07:50), 1.4.9 (2022-05-09 10:40), 1.5.0 (2022-11-12 09:30), 1.5.1 (2023-01-05 22:50), 1.5.2 (2023-09-10 02:00), 1.5.3 (2023-12-02 01:40), 1.5.4 (2024-07-17 19:00)
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