Package: extremefit 1.0.2

extremefit: Estimation of Extreme Conditional Quantiles and Probabilities

Extreme value theory, nonparametric kernel estimation, tail conditional probabilities, extreme conditional quantile, adaptive estimation, quantile regression, survival probabilities.

Authors:Gilles Durrieu, Ion Grama, Kevin Jaunatre, Quang-Khoai Pham, Jean-Marie Tricot

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extremefit.pdf |extremefit.html✨
extremefit/json (API)

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

Peer review:

Datasets:

On CRAN:

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

3.07 score 1 stars 1 packages 39 scripts 380 downloads 44 exports 0 dependencies

Last updated 6 years agofrom:4b89fb756d. Checks:ERROR: 1 NOTE: 2 OK: 4. Indexed: yes.

TargetResultDate
Doc / VignettesFAILNov 14 2024
R-4.5-winNOTENov 14 2024
R-4.5-linuxNOTENov 14 2024
R-4.4-winOKNov 14 2024
R-4.4-macOKNov 14 2024
R-4.3-winOKNov 14 2024
R-4.3-macOKNov 14 2024

Exports:bandwidth.CVbandwidth.gridBiweight.kernelbootCIbootCI.tscox.adaptCriticalValuedburrdparetodparetomixEpa.kernelGaussian.kernelgoftestgoftest.hill.adaptgoftest.hill.tshillhill.adapthill.tspburrplot.hillplot.hill.adaptpparetopparetoCPpparetomixpredict.cox.adaptpredict.hillpredict.hill.adaptpredict.hill.tsprint.hill.tsprobgridqburrqparetoqparetoCPqparetomixrburrrburr.dependentRectangular.kernelrparetorparetoCPrparetomixTriang.kernelTruncGauss.kernelwecdfwquantile

Dependencies:

extremefit: Estimation of extreme quantiles and probabilities of rare events

Rendered fromextremefit.ltxusingR.rsp::texon Nov 14 2024.

Last update: 2018-12-19
Started: 2018-12-19

Readme and manuals

Help Manual

Help pageTopics
Choice of the bandwidth by cross validation.bandwidth.CV
Bandwidth Gridbandwidth.grid
Biweight kernel functionBiweight.kernel
Pointwise confidence intervals by bootstrapbootCI
Pointwise confidence intervals by bootstrapbootCI.ts
Burr distributionBurr Distribution dburr pburr qburr rburr
Compute the extreme quantile procedure for Cox modelcox.adapt
Computation of the critical value in the hill.adapt functionCriticalValue
High-frequency noninvasive valvometry datadataOyster
Wind speed for Brest (France)dataWind
Epanechnikov kernel functionEpa.kernel
Gaussian kernel functionGaussian.kernel
Goodness of fit test statisticsgoftest
Goodness of fit test statisticsgoftest.hill.adapt
Goodness of fit test statistics for time seriesgoftest.hill.ts
Hill estimatorhill
Compute the extreme quantile procedurehill.adapt
Compute the extreme quantile procedure on a time dependent datahill.ts print.hill.ts
Load curve of an habitationLoadCurve
Pareto distributiondpareto Pareto Distribution ppareto qpareto rpareto
Pareto mixture distributiondparetomix Pareto mix pparetomix qparetomix rparetomix
Hill plotplot.hill
Hill.adapt plotplot.hill.adapt
Pareto change point distributionpparetoCP qparetoCP rparetoCP
Predict the survival or quantile function from the extreme procedure for the Cox modelpredict.cox.adapt
Predict the adaptive survival or quantile functionpredict.hill
Predict the adaptive survival or quantile functionpredict.hill.adapt
Predict the adaptive survival or quantile function for a time seriepredict.hill.ts
Probability gridprobgrid
Generate Burr dependent datarburr.dependent
Rectangular kernel functionRectangular.kernel
Triangular kernel functionTriang.kernel
Truncated Gaussian kernel functionTruncGauss.kernel
Weighted empirical cumulative distribution functionwecdf
Weighted quantilewquantile