R package evir: Extreme Values in R. Functions for extreme value theory, which may be divided into the following groups; exploratory data analysis, block maxima, peaks over thresholds (univariate and bivariate), point processes, gev/gpd distributions.
Keywords for this software
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Bee, M.: Density approximations and VaR computation for compound Poisson-lognormal distributions (2017)
- Reynkens, Tom; Verbelen, Roel; Beirlant, Jan; Antonio, Katrien: Modelling censored losses using splicing: a global fit strategy with mixed Erlang and extreme value distributions (2017)
- Chan, Stephen; Nadarajah, Saralees; Afuecheta, Emmanuel: An R package for value at risk and expected shortfall (2016)
- Eric Gilleland and Richard Katz: extRemes 2.0: An Extreme Value Analysis Package in R (2016)
- Miljkovic, Tatjana; Grün, Bettina: Modeling loss data using mixtures of distributions (2016)
- Gilleland, Eric; Ribatet, Mathieu; Stephenson, Alec G.: A software review for extreme value analysis (2013)
- Gonzalez, Juan; Rodriguez, Daniela; Sued, Mariela: Threshold selection for extremes under a semiparametric model (2013)
- Nadarajah, Saralees; Afuecheta, Emmanuel; Chan, Stephen: A double generalized Pareto distribution (2013)
- Pfaff, Bernhard: Financial risk modelling and portfolio optimization with R (2013)
- Ruckdeschel, Peter; Horbenko, Nataliya: Optimally robust estimators in generalized Pareto models (2013)
- Ferrari, Davide; Paterlini, Sandra: The maximum $L_q$-likelihood method: an application to extreme quantile estimation in finance (2009)