R package evd: Functions for extreme value distributions. Extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.
Keywords for this software
References in zbMATH (referenced in 12 articles )
Showing results 1 to 12 of 12.
- Punzo, Antonio; Bagnato, Luca; Maruotti, Antonello: Compound unimodal distributions for insurance losses (2018)
- Yang Hu; Carl Scarrott: evmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density Estimation (2018) not zbMATH
- Kojadinovic, Ivan; Naveau, Philippe: Detecting distributional changes in samples of independent block maxima using probability weighted moments (2017)
- Eric Gilleland and Richard Katz: extRemes 2.0: An Extreme Value Analysis Package in R (2016) not zbMATH
- Yuen, Robert; Stoev, Stilian: CRPS M-estimation for max-stable models (2014)
- Bee, Marco: A maximum entropy approach to loss distribution analysis (2013)
- Gilleland, Eric; Ribatet, Mathieu; Stephenson, Alec G.: A software review for extreme value analysis (2013)
- Cooley, Daniel; Davis, Richard A.; Naveau, Philippe: Approximating the conditional density given large observed values via a multivariate extremes framework, with application to environmental data (2012)
- Gudendorf, Gordon; Segers, Johan: Nonparametric estimation of multivariate extreme-value copulas (2012)
- Gudendorf, Gordon; Segers, Johan: Nonparametric estimation of an extreme-value copula in arbitrary dimensions (2011)
- Bacro, Jean-Noël; Bel, Liliane; Lantuéjoul, Christian: Testing the independence of maxima: from bivariate vectors to spatial extreme fields: asymptotic independence of extremes (2010)
- Yee, Thomas W.; Stephenson, Alec G.: Vector generalized linear and additive extreme value models (2007)