# mev v.1.14
New:
- bivariate coefficient of extremal asymmetry
- four new families of max-stable models (pairwise beta, pairwise
exponential, weighted Dirichlet and weighted exponential) for rmev,
following Ballani and Schlather (2011)
- maximum likelihood estimation routines (
fit.gpd,
fit.gev, etc.) now accept fixed parameters
- mean residual life plots with weighted least square fit
- coefficient of variation tests for threshold selection
- Varty et al. metric based threshold selection diagnostic
- anova methods for
mev_gpd and mev_gev
objects
rmev and rmevspec now accept a distance
matrix in place of coordinates for spatial models.- new datasets
- website with vignettes
Changes
- Functions W.diag and NC.diag now have S3 plot and print methods
- Changes to arguments (backward compatible) to xdat throughout
- Many dependencies used by single functions are now listed in
Suggest.
Fixes:
- ext.coef correctly handles arrays with missing values (reported by
M. Jousset)
- Optimization method in fit.gev now uses the PWM solution of Hosking
(1985) as starting value
- gev.pll now returns confidence intervals for param = “quant”
(reported by D. Dupuis)
- Fixes to NHPP order statistics density (returns -Inf outside of
domain, also correctly evaluate for boundary case when xi=-1)
- Optimization routines fit.pp, fit.gev and fit.rlarg now return
correct MLE when solution lies on boundary (xi=-1) and are more robust
to failure (gradients for nlminb return large values rather than NAs
which caused the algorithm to stop).
- Grimshaw’s algorithm sometimes returned incorrect value because of
too low tolerance for eta near zero. Set back to default settings.
- fit.gpd(…, method = “obre”) now returns additional failure messages
if the algorithm drifts towards infeasible values.
- rparp now correctly handles xi=0
- Extended GP model now has ‘step’ for discretization, and a valid
distribution function that returns real arguments whenever the input is
finite (#9)
- W.diag and egp.fitrange include arguments for changing ‘par’
(#10)
- smith.penult now computes reciprocal hazard and it’s derivative on
the log scale (when possible) to avoid numerical overflow.
# mev v.1.13 (Release date:
2019-12-17)
Fixes:
- rlarg.infomat incorrect sign for expected information for d=1
- rmev function did not work for
alog and
aneglog (reported by Michael Lalancette)
- Remove class()!= “matrix due to changes in R 4.0.0
- egp.retlev now returns invisible object (new ordering and
format).
Changes:
- New S3 methods for objects returned by “fit” routines, for use in
“lax” package
# mev v.1.12 (Release date:
2019-06-24)
New:
- Function ‘taildep’ is multivariate equivalent to ‘evd::chiplot’
- Function ‘rparpcs’ for simulating from elliptical Pareto processes
associated with max
- ‘rgparp’ for simulation of generalized R Pareto processes
- Exponent measure for Brown-Resnick and extremal Student model
- ‘spunif’ for semi-parametric transform to uniform (tail modelled
using GP)
- ‘rparp’ now has attributes to give acceptance rate of accept/reject
procedure.
- Exponent measure estimators ‘extcoef’
- New method for robust OBRE estimates of GP parameters
- Functions ‘fit.gev’,‘fit.gpd’, ‘fit.rlarg’ and ‘fit.pp’ for maximum
likelihood estimation
- Default printing and plot optims (p-p and q-q plots) for mev_
objects
- Changes to optimization routine for pp in ‘W.diag’ function, use of
expected information matrix, change to default tuning parameter
- New datasets: eskrain, maiquetia, nidd, venice, w1500m
Fixes:
- Scaling of Brown-Resnick is now consistent with literature (half of
semivariogram)
- Degrees of freedom argument in C++ code for ‘rmev’ with extremal
Student family was incorrect
- ‘rparp’ now has a hard bound to ensure the vector of simulated
vectors fits in memory.
- Change to Grimshaw routine to ensure shape not less than -1,
constrained optimization method
- Information matrix, score for GEV now interpolated in a neighborhood
of zero to preserve continuity and avoid numerical overflow.
- Information matrix of GEV: scale factor off. All scores and
information matrix have been checked and limits as xi -> 0
implemented.
- ext.index number of exceedances off by one, causing Inf in weight
vector for lm (thanks to @MCristinaMiranda). Warnings now
silenced by default.
Changes:
- coordinates for rmev, rparp, etc. now use
coord instead
of loc to avoid confusion with location parameter in
rgparp
- Removed dependency to ‘ismev’, ‘rootsolve’ (replaced with ‘nleqslv’
routine) and ‘numDeriv’.
- Change to plot for profile log-likelihood methods
- ‘smith.penult’ function has new arguments (backward compatible). The
quantiles ‘u’ are now returned for Smith penultimate approximations with
‘method = “pot”’
# mev v.1.11 (Release date:
2018-02-23)
New:
- 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
Changes:
- 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 (thanks to A. Stephenson)
Fixes:
- Fixed incorrect scaling in ‘infomat.test’ (thanks to P.
Northrop)
- 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)
New:
- Added ‘negdir’ model to rmev
Changes:
- Fixed argument matching in function ‘egp2’
# mev v.1.9x
New:
- Changes to angmeas to include different weighting if the region of
interest is ‘max’ or ‘min’
Fixes:
- Fixed bug affecting angmeas in the bivariate case that would cause
the method to crash
# mev v.1.8x
New:
- Bias-correction, TEM added
- Penultimate approximations (Papastathopoulos & Tawn, 2013),
Naveau et al. (2014) and Smith (1987)
Changes:
- model “br” is now distinct from “hr”
Fixes:
- fixed invalid random number generation from logistic model for
near-independence cases
# mev v1.7 (Release date:
2016-06-07)
New:
- ext.index Extremal index estimates based on interexceedance and gap
times
- infomat.test Information matrix test of Suveges and Davison
(2010)
Fixes:
- fixed an error in the acceptance rate for the
gp.fit
MCMC
# mev v1.6.1 (Release date:
2016-03-15)
Fixes:
- 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)
New:
*Empirical and Euclidean likelihood estimation of spectral
measure
Changes:
*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)
New:
- 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)
Fixes:
- fixed error for simulation on grids
Changes:
- check for marginal mean constraint for the Dirichlet mixture now has
tolerance
# mev v1.3 (Release date:
2015-10-05)
Changes:
- 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)
Changes:
- Added the negative bilogistic and the scaled Dirichlet models.
- Extremal Dirichlet model implemented with “sm” only.
# mev v1.1 (Release date:
2015-08-19)
Changes:
- 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)