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>.">

evgam: Generalised Additive Extreme Value Models (original) (raw)

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>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.8.3), mgcv
LinkingTo: Rcpp, RcppArmadillo
Published: 2022-06-28
DOI: 10.32614/CRAN.package.evgam
Author: Ben Youngman
Maintainer: Ben Youngman <b.youngman at exeter.ac.uk>
License: GPL-3
NeedsCompilation: yes
Citation: evgam citation info
Materials: NEWS
In views: ExtremeValue
CRAN checks: evgam results

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