Package: evdbayes 1.1-3
Alec Stephenson
evdbayes: Bayesian Analysis in Extreme Value Theory
Provides functions for the Bayesian analysis of extreme value models, using Markov chain Monte Carlo methods. Allows the construction of both uninformative and informed prior distributions for common statistical models applied to extreme event data, including the generalized extreme value distribution.
Authors:
evdbayes_1.1-3.tar.gz
evdbayes_1.1-3.tar.gz(r-4.5-noble)evdbayes_1.1-3.tar.gz(r-4.4-noble)
evdbayes_1.1-3.tgz(r-4.4-emscripten)evdbayes_1.1-3.tgz(r-4.3-emscripten)
evdbayes.pdf |evdbayes.html✨
evdbayes/json (API)
| # Install 'evdbayes' in R: |
| install.packages('evdbayes', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- rainfall - Daily Aggregate Rainfall
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:b0b2783d9e. Checks:2 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 14 2025 |
| R-4.5-linux-x86_64 | OK | Feb 14 2025 |
Exports:ar.choicedpostdprior.loglognormdprior.normdprior.probdprior.quantgevlikgevlik2gibbsgpdlikgpdlik2ibetaigammamc.quantmposterioroslikoslik2posteriorpplikpplik2prior.loglognormprior.normprior.probprior.quantrl.predrl.pst
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute Suited Proposal Standard Deviations | ar.choice |
| Information for Beta and Gamma Distributions | ibeta igamma |
| Calculate Log-likelihoods | gevlik gpdlik oslik pplik |
| Compute GEV Quantiles from Markov Chains | mc.quant |
| Maximizing Posterior Distributions | mposterior |
| MCMC Sampling of Posterior Distributions | posterior |
| Construction of Prior Distributions | prior.loglognorm prior.norm prior.prob prior.quant |
| Daily Aggregate Rainfall | rainfall |
| Return Level Plots for GEV Predictive Distributions | rl.pred |
| Return Level Plots Depicting Distributions of GEV Quantiles | rl.pst |