Package: hkevp 1.1.6
hkevp: Spatial Extreme Value Analysis with the Hierarchical Model of Reich and Shaby (2012)
Several procedures for the hierarchical kernel extreme value process of Reich and Shaby (2012) <doi:10.1214/12-AOAS591>, including simulation, estimation and spatial extrapolation. The spatial latent variable model <doi:10.1214/11-STS376> is also included.
Authors:
hkevp_1.1.6.tar.gz
hkevp_1.1.6.zip(r-4.7)hkevp_1.1.6.zip(r-4.6)hkevp_1.1.6.zip(r-4.5)
hkevp_1.1.6.tgz(r-4.6-x86_64)hkevp_1.1.6.tgz(r-4.6-arm64)hkevp_1.1.6.tgz(r-4.5-x86_64)hkevp_1.1.6.tgz(r-4.5-arm64)
hkevp_1.1.6.tar.gz(r-4.7-arm64)hkevp_1.1.6.tar.gz(r-4.7-x86_64)hkevp_1.1.6.tar.gz(r-4.6-arm64)hkevp_1.1.6.tar.gz(r-4.6-x86_64)
hkevp_1.1.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
hkevp/json (API)
| # Install 'hkevp' in R: |
| install.packages('hkevp', repos = c('https://lbelzile.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lbelzile/hkevp/issues
Last updated from:daabb1ab8b. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 116 | ||
| linux-devel-x86_64 | OK | 144 | ||
| source / vignettes | OK | 130 | ||
| linux-release-arm64 | OK | 140 | ||
| linux-release-x86_64 | OK | 113 | ||
| macos-release-arm64 | OK | 115 | ||
| macos-release-x86_64 | OK | 193 | ||
| macos-oldrel-arm64 | OK | 77 | ||
| macos-oldrel-x86_64 | OK | 189 | ||
| windows-devel | OK | 125 | ||
| windows-release | OK | 109 | ||
| windows-oldrel | OK | 105 | ||
| wasm-release | OK | 122 |
Exports:extrapol.gevextrapol.return.levelhkevp.expmeasurehkevp.fithkevp.predicthkevp.randlatent.fitmcmc_deponlymcmc_hkevpmcmc_latentmcmc.funmcmc.plotreturn.level
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Spatial extrapolation of GEV parameters with the HKEVP | extrapol.gev |
| Spatial extrapolation of a return level. | extrapol.return.level |
| A hierarchical model for spatial extreme values | hkevp-package hkevp |
| Exponent measure of the HKEVP | hkevp.expmeasure |
| Fitting procedure of the HKEVP with MCMC algorithm | hkevp.fit |
| Predictive distribution of the max-stable process at target positions. | hkevp.predict |
| Simulation of the HKEVP | hkevp.rand |
| Fitting procedure of the latent variable model | latent.fit |
| Point estimates of HKEVP fit | mcmc.fun |
| Markov chains plotting | mcmc.plot |
| The associated return level | return.level |
