R-Forge Project News

ViewVC Repository browsing is back.

Amando Zanderigo — 2023-08-24T12:29:32+00:00

I have fixed the ViewVC respository browsing. If you notice any problems with it, please contact us at R-Forge@R-Project.org.

Maintenance (4-5 April)

Amando Zanderigo — 2023-04-03T12:34:49+00:00

Ongoing maintenance will result in additional downtime on the 4th (and possibly 5th) of April. We apologize for the inconvenience.

Further Maintenance (23-24 March 2023)

Amando Zanderigo — 2023-03-21T09:39:14+00:00

Further maintenance will be performed on 23-24 March, 2023. Please do not make changes to projects during this time.

For questions, please contact: R-Forge@R-Project.org

We apologise for any inconvenience.

Maintenance (16-17 March)

Amando Zanderigo — 2023-03-13T08:45:07+00:00

Dear R-Forge users,

System maintenance is planned for 16 - 17 March.

R-Forge will be down during this period.

The system will be backed up, however we do not recommend submitting changes to projects shortly prior to this period.

For any questions, please contact: R-Forge@R-Project.org

R-Forge Admin

ssh-ed25519 keys

Gennadiy Starostin — 2020-12-11T14:30:47+00:00

Dear users, you may now use ssh-ed25519 keys with R-Forge (ssh keys are managed in "My Account" settings).
Best regards,
R-Forge Team.

Surveillance package is part of the Covid-19 outbreak response

Michael Höhle — 2020-05-04T05:56:20+00:00

The nowcast function of the surveillance package is used to provide situational awareness during the Covid-19 outbreak. This is a collaboration between Stockholm University, the LMU Munich and the LGL Bavaria.

For further details see the site https://corona.stat.uni-muenchen.de/ and the accompanying manuscript by Guenther et al. (2020) [1]. The nowcasts provide the basis of effective reproduction number calculations.

[1] https://www.stablab.stat.uni-muenchen.de/_assets/docs/nowcasting_covid19_bavaria.pdf

Submission to CRAN

Gennadiy Starostin — 2019-08-13T07:25:14+00:00

Dear R-Forge users, submission to CRAN works as usual now. If you tried to submit a package from R-Forge to CRAN since July 16, you might need to resubmit it. Please note however, that the submission team is on vacation, so the submitted packages will wait in the queue till August 19.
Best regards,
R-Forge Team.

Maintenance: APR, 17-18

Gennadiy Starostin — 2019-04-03T08:28:48+00:00

Dear R-Forge users, during the upcoming maintenance all of the services will be unavailable. The expected downtime is 17 - 18 APR.
Best regards,
R-Forge Team.

depmixS4 version 1.4 on r-forge with standard errors

Ingmar Visser — 2019-01-14T07:17:02+00:00

The 1.4 version of depmixS4 has an important (and much requested) new feature: the possibility to request standard errors of estimated parameters through the use of a finite differences approximation of the hessian. Comments and feedback much appreciated! After some time in this beta version we will post the new version to CRAN as well.
Ingmar Visser & Maarten Speekenbrink

RobASt release 1.1

Peter Ruckdeschel — 2018-08-20T07:26:01+00:00

Updates for the packages of the RobASt family are now avaialable on CRAN in
version >= 1.1.0

Most importantly, we have (finally) released on CRAN a (long announced) new
package

"RobExtremes"

in the RobASt family of packages.

+ It provides (speeded up) optimally-robust estimators [MBRE, OMSE, RMXE]
for Generalized Extreme Value [GEV] distributions, Generalized Pareto
distributions [GPD], Pareto distributions,
+ As other examples of L2 differentiable Scale-shape families, it also
provides these (speeded up) estimators for Weibull and Gamma
distributions.
+ It has robust (high-breakdown) starting estimators for
- GPD (PickandsEstimator, medkMAD, medSn, medQn)
- GEV (PickandsEstimator)
- Pareto (Cramér-von-Mises-Minimum-Distance-Estimator)
- Weibull (the quantile based estimator of Boudt/Caliskan/Croux)
+ For all these families, of course, MLEs and Minimum-Distance-Estimators
are also available through package distrMod
+ We bridge to the diagnostics provided by package ismev, i.e. our
return objects can be plugged into the diagnostics of this package
+ We have the usual diagnostic plots from package RobAStBase, i.e.
- Outylingness plots
- IC plots
- Information plots
- compareIC plots
- Cniperpoint plots (from ROptEst)
but also (adopted from package distrMod)
- qqplots (with confidence bands)
- returnlevel plots
+ As a starting point you may look at the included script
"RobFitsAtRealData.R" in the scripts folder of the package,
accessible by
file.path(system.file(package="RobExtremes"),
"scripts/RobFitsAtRealData.R")

This is joint work with Nataliya Horbenko (whose PhD thesis went into this
package to a large extent), nataliya.horbenko@gmail.de, with contributions
by Dasha Pupashenko, Misha Pupashenko, Gerald Kroisandt, Eugen Massini,
Sascha Desmettre and Bernhard Spangl in the framework of project
"Robust Risk Estimation" (2011-2016) funded by Volkswagen foundation
(and gratefully ackknowledged). Thanks also goes to the maintainers of CRAN,
in particully to Uwe Ligges who greatly helped us with finding an appropriate
way to store the database of interpolating functions which allow the speed up
-- this is now package RobAStRDA on CRAN.

References
N. Horbenko, P. Ruckdeschel, T. Bae (2011): Robust Estimation of Operational
Risk. Journal of Operational Risk 6(2), 3-30.
Ruckdeschel, P. and Horbenko, N. (2011): Optimally-Robust Estimators in
Generalized Pareto Models. Statistics. 47(4), 762–791.
Ruckdeschel, P. and Horbenko, N. (2012): Yet another breakdown point notion:
EFSBP –illustrated at scale-shape models. Metrika, 75(8), 1025–1047.

=================================================================================
In the other packages of the RobASt family of pkgs, the most important changes are:

As in distr 2.7, wherever possible we now use q.l internally instead of q to
provide functionality in IRKernel

RobAStBase:
- we enhanced our diagnostic plots:
+ all diagnostics (including qqplot and returnlevelplot) have adopted the same
argument naming (and selection paradigm)
the suffix is .lbs instead of .lbl,
the attributes of shown points have ending .pts
the observations are classed into three groups:
- the labelled observations selected through which.lbs and which.Order
- the shown non labelled observations (which are not in the previous set)
selected by which.nonlbs
- the non-shown observations (the remaining ones not contained in the former 2 grps)
-> point attributes may either refer to prior selection or to post-selection in
which case we have .npts variants
+ wherever possible arguments are vectorized to allow point - individual attributes
+ plot methods now return an S3 object of class \code{c("plotInfo","DiagnInfo")},
i.e., a list containing the information needed to produce the respective plot,
which at a later stage could be used by different graphic engines (like, e.g.
\code{ggplot}) to produce the plot in a different framework.
+ new methods for returnlevelplot for RobModel, InfRobModel, kStepEstimate (as qqplot)
ROptEst:
+ new wrapper functions RMXEstimator, OBREstimator, MBREstimator, OMSEstimator
+ several tweaks to speed up things:
- optIC gains argument withMakeIC
- roptest gains argument withMakeIC
- getStartIC-methods gain argument withMakeIC
- getRiskIC and getBiasIC gain argument withCheck
RobAStRDA:
+ the Lagrange multiplier interpolaters allowing for speed up in our opt-robust
estimators have been re-built as the current .rda file was corrupted

For details please see the NEWS files in the packages, available as
NEWS("<pkgname>").

Best regards from the main developpers & maintainers,
Peter Ruckdeschel (peter.ruckdeschel@uni-oldenburg.de) &
Matthias Kohl (matthias.kohl@stamats.de)