Package: evgam 1.0.0

Ben Youngman

evgam: Generalised Additive Extreme Value Models

Methods for fitting various extreme value distributions with parameters of generalised additive model (GAM) form are provided. For details of distributions see Coles, S.G. (2001) <doi:10.1007/978-1-4471-3675-0>, GAMs see Wood, S.N. (2017) <doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. & Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>. Details of how evgam works and various examples are given in Youngman, B.D. (2022) <doi:10.18637/jss.v103.i03>.

Authors:Ben Youngman

evgam_1.0.0.tar.gz
evgam_1.0.0.tar.gz(r-4.5-noble)evgam_1.0.0.tar.gz(r-4.4-noble)
evgam_1.0.0.tgz(r-4.4-emscripten)evgam_1.0.0.tgz(r-4.3-emscripten)
evgam.pdf |evgam.html
evgam/json (API)
NEWS

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • COelev - Colorado daily precipitation accumulations
  • COprcp - Colorado daily precipitation accumulations
  • COprcp_meta - Colorado daily precipitation accumulations
  • FCtmax - Fort Collins, Colorado, US daily max. temperatures
  • fremantle - Annual Maximum Sea Levels at Fremantle, Western Australia

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

3.76 score 11 packages 111 scripts 1.6k downloads 11 exports 6 dependencies

Last updated 2 years agofrom:e2d6020708. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 04 2024
R-4.5-linux-x86_64NOTEDec 04 2024

Exports:colplotdfbinddfrunmaxevgamextremalfevgamginv.evgampinvqevrunmaxseq_between

Dependencies:latticeMatrixmgcvnlmeRcppRcppArmadillo