Multivariate Extreme Value Distributions
Exact simulation from max-stable processes and multivariate extreme value distributions for various parametric models. Threshold selection methods.
Multivariate Extreme Value distributions
R-package to perform simulations from multivariate extreme value models. The package also includes
some routine functions for univariate analysis, notably threshold selection diagnostics, optimization
for the generalized Pareto distribution, bias-correction and tangent exponential model approximations,
non-parametric spectral measure estimation using empirical likelihood methods, etc.
mev v.1.11 (Release date: 2018-02-23)
- Function 'rparp' for simulation from R-Pareto Processes via rejection sampling
- Function 'gev.pll' and 'gpd.pll' for penalized profile likelihood and tangent exponential model approximations
- New functions 'chibar', 'angextrapo' and 'lambdadep' for bivariate and multivariate model estimation, based on work of Tawn et al.
- Dirichlet mixture smoothing for empirical angular distribution of de Carvalho et al. (2013)
- Functions 'gev.mle' and 'gpd.mle' for maximum likelihood estimates of transformed parameters
- Functions 'gev.abias' and 'gpd.abias' for asymptotic bias of block maxima for fixed sample sizes or fixed thresholds
- Functions 'rmev', 'rmevspec', etc. now only accept variogram functions
vario that have distance as argument
- Simulation from 'rmev' and 'rmevspec' faster to refactoring of code
- Function 'smith.penult' now has a 'family' as argument for specifying distributions via a string
- Function 'gev.tem' and 'gpd.tem' are now a wrapper for 'gev.pll' and 'gpd.pll', respectively. Routine should be more robust
- TEM corrections now handle more options
- Clarifications in the vignette about the asymmetric negative logistic model following a discussion with A. Stephenson.
- Fixed incorrect scaling in 'infomat.test' (thanks to P. Northrop for pointing the latter)
- Model "br" now simulates from stationary version only if argument 'sigma' is provided, and otherwise samples intrinsically Gaussian processes
- Display of p-value matrix for 'infomat.test'
mev v.1.10 (Release date: 2017-02-01)
- Added 'negdir' model to rmev
- Fixed argument matching in function
- Changes to angmeas to include different weighting if the region of interest is
- Fixed bug affecting angmeas in the bivariate case that would cause the method to crash
- Bias-correction, TEM added
- Penultimate approximations (Papastathopoulos & Tawn, 2013), Naveau et al. (2014) and Smith (1987)
- model "br" is now distinct from "hr"
- fixed invalid random number generation from logistic model for near-independence cases
mev v1.7 (Release date: 2016-06-07)
- fixed an error in the acceptance rate for the gp.fit MCMC
- ext.index Extremal index estimates based on interexceedance and gap times
- infomat.test Information matrix test of Suveges and Davison (2010)
mev v1.6.1 (Release date: 2016-03-15)
- fixed an error in the normal sampler (affecting version 1.5 and 1.6)
All simulations of Brown-Resnick or extremal-Student were affected by the mistake
mev v1.6 (Release date: 2016-03-08)
*Empirical and Euclidean likelihood estimation of spectral measure
*gp.fit ample changes to the function, in particular a fix for the printing method, handling of errors and inclusion of the Zhang (2010) method and MCMC algorithm for the latter. This function is still preliminary and may updated in the nearby future to include further possibilities.
mev v1.5 (Release date: 2016-02-16)
- Wadsworth (2015) Technometrics's proposal for threshold selection based on NHPP superposition
- Northrop & Coleman diagnostic (2014) Extremes for shape equality and p-value path
mev v1.4 (not on CRAN)
- fixed error for simulation on grids
- check for marginal mean constraint for the Dirichlet mixture now has tolerance
mev v1.3 (Release date: 2015-10-05)
- Extremal Dirichlet model now implemented with "ef"
- Added Smith and asymmetric (negative) logistic model (differs from bivariate setting for aneglog, given that the later is not a valid DF according to Stephenson).
- rmev can now return arrays for random fields on regular grids ("hr","exstud" and "smith" models).
mev v1.2 (Release date: 2015-08-23)
- Added the negative bilogistic and the scaled Dirichlet models.
- Extremal Dirichlet model implemented with "sm" only.
mev v1.1 (Release date: 2015-08-19)
- Implementation of sampler from spectral distribution, moving rdirspec and rbilogspec to background along with other functions.
- Fixed a typo in rPextstud setting arguments of newly created arma vector to zero
mev v1.0 (Release date: 2014-08-16)