Package: hkevp 1.1.5

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:Quentin Sebille <[email protected]>

hkevp_1.1.5.tar.gz
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hkevp.pdf |hkevp.html✨
hkevp/json (API)

# Install 'hkevp' in R:
install.packages('hkevp', repos = c('https://lbelzile.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/lbelzile/hkevp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

13 exports 0.63 score 2 dependencies 10 scripts 226 downloads

Last updated 1 years agofrom:1e058265c5. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-win-x86_64OKSep 07 2024
R-4.5-linux-x86_64OKSep 07 2024
R-4.4-win-x86_64OKSep 07 2024
R-4.4-mac-x86_64OKSep 07 2024
R-4.4-mac-aarch64OKSep 07 2024
R-4.3-win-x86_64OKSep 07 2024
R-4.3-mac-x86_64OKSep 07 2024
R-4.3-mac-aarch64OKSep 07 2024

Exports:extrapol.gevextrapol.return.levelhkevp.expmeasurehkevp.fithkevp.predicthkevp.randlatent.fitmcmc_deponlymcmc_hkevpmcmc_latentmcmc.funmcmc.plotreturn.level

Dependencies:RcppRcppArmadillo