Package: mevr 1.2.3

mevr: Fitting the Metastatistical Extreme Value Distribution MEVD

Extreme value analysis with the metastatistical extreme value distribution MEVD (Marani and Ignaccolo, 2015, <doi:10.1016/j.advwatres.2015.03.001>) and some of its variants. In particular, analysis can be performed with the simplified metastatistical extreme value distribution SMEV (Marra et al., 2019, <doi:10.1016/j.advwatres.2019.04.002>) and the temporal metastatistical extreme value distribution TMEV (Falkensteiner et al., 2023, <doi:10.1016/j.wace.2023.100601>). Parameters can be estimated with probability weighted moments, maximum likelihood and least squares. The data can also be left-censored prior to a fit. Density, distribution function, quantile function and random generation for the MEVD, SMEV and TMEV are included. In addition, functions for the calculation of return levels including confidence intervals are provided. For a description of use cases please see the provided references.

Authors:Harald Schellander [aut, cre], Alexander Lieb [ctb], Marc-Andre Falkensteiner [ctb]

mevr_1.2.3.tar.gz
mevr_1.2.3.zip(r-4.7)mevr_1.2.3.zip(r-4.6)mevr_1.2.3.zip(r-4.5)
mevr_1.2.3.tgz(r-4.6-any)mevr_1.2.3.tgz(r-4.5-any)
mevr_1.2.3.tar.gz(r-4.6-any)mevr_1.2.3.tar.gz(r-4.5-any)
mevr_1.2.3.tgz(r-4.5-emscripten)
mevr.pdf |mevr.html
mevr/json (API)
NEWS

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

Bug tracker:https://github.com/haraldschellander/mevr/issues

Pkgdown/docs site:https://haraldschellander.github.io

Datasets:

On CRAN:

Conda:

extreme-value-statistics

3.00 score 2 stars 1 scripts 276 downloads 16 exports 49 dependencies

Last updated from:97c94567b5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK192
source / vignettesOK173
linux-release-x86_64OK187
macos-release-arm64OK119
macos-oldrel-arm64OK108
windows-develOK165
windows-releaseOK183
windows-oldrelOK185
wasm-releaseOK119

Exports:censored_weibull_fitdmevdtmevevent_separationfmevfsmevftmevordinary_eventspmevpp.weibullptmevqmevqtmevreturn.levels.mevrmevweibull_tail_test

Dependencies:bamlssBHclicodacodetoolscolorspacecpp11data.tabledistributions3doParalleldplyrEnvStatsfarverforeachFormulagenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixMBAmgcvmmandmvtnormnlmenortestpillarpkgconfigR6RColorBrewerRcpprlangS7scalesspsurvivaltibbletidyselectutf8vctrsviridisLitewithr