Package: hkevp 1.1.6

Leo Belzile

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 [aut], Leo Belzile [cre]

hkevp_1.1.6.tar.gz
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://cran.r-universe.dev', 'https://cloud.r-project.org'))

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:

Conda:

openblascppopenmp

1.00 score 10 scripts 237 downloads 13 exports 2 dependencies

Last updated from:49db3e70d3. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK171
linux-devel-x86_64OK123
source / vignettesOK199
linux-release-arm64OK121
linux-release-x86_64OK104
wasm-releaseOK100

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

Dependencies:RcppRcppArmadillo