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RobExtremes

1.3.2Package record

Optimally Robust Estimation for Extreme Value Distributions

0packages depend
3.2Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

Optimally robust estimation for extreme value distributions using S4 classes and methods (based on packages 'distr', 'distrEx', 'distrMod', 'RobAStBase', and 'ROptEst'); the underlying theoretic results can be found in Ruckdeschel and Horbenko, (2013 and 2012), \doi{10.1080/02331888.2011.628022} and \doi{10.1007/s00184-011-0366-4}.

Changes in 1.3.2

#######################################

under the hood:

  • adapted reference output for new startupmsg

#######################################

From inst/NEWS in the release

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTERd contentsr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Rd files without \usage:
  ‘internal-methods.Rd’
\arguments should not be documented without \usage.

CRAN check page ↗

Slowest check: 4.7 min · r-devel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE12 OK, 1 NOTE2026-07-11
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.3.2
READMENoVignettesNoNEWSYes · 100% structured · mentions 1.3.2Citation fileYes · computed when R runs itWebsitenot declared in DESCRIPTION
Help pages
44 (5 internal)includes a package overview page
Examples that run
97%32 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
95%
Return-value docs
87%
Help pages citing references
45%

Downloads

3.2K
CRAN downloads in the past year
Rank #15,488 · ~9/day · ~269/mo
Daily download trend is not available in this view yet.
30230 days
79790 days
3.2K1 year
Compare downloads with other packages →
Also on339 r2u6 autocran

Repository

PracticesBeta

Repository r-forge.r-project.org/projects/robast is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
13 external dependencies (excludes base and recommended)

Installing RobExtremes adds 17 packages (9 with compiled code, 14 MB of source tarballs). Heaviest: RobAStRDA 3.4 MB, robustbase 2.2 MB, distrEx 2.1 MB.

Depends (6)
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (8)
Maintainer since 1.1.0 (2018), Author, Copyright holder
Author, Copyright holder
Author, Copyright holder
Contributor
contributed smoothed grid values of the Lagrange multipliers
Contributor
contributed testing routines
Contributor
contributed an interactive smoothing routine for smoothing the Lagrange multipliers and smoothed grid values of the…
Contributor
contributed MDE-estimation for GEV distribution in the framework of her PhD thesis 2011--14
Contributor
contributed smoothed grid values of the Lagrange multipliers
Releases (5)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.3.2Latest
    record
    2025-01-15 · current release · diff ↗
  • 1.3.1
    record
    2024-09-04 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • unarchivedReturned to CRAN
    2024-02-09
  • 1.3.0
    record
    2024-02-09 · diff ↗
  • archivedRemoved from CRAN
    2024-01-12
    issues were not corrected in time
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 1.2.0
    record
    2019-04-08 · diff ↗
  • 1.1.0
    record
    2018-08-03
  • R
    R 3.5.0 released · 2018-04-23

Package metadata

First published
2018-08-03
Total releases
5 / 8 yrs
License
LGPL-3 OSI
Minimum R
≥ 3.4
Download size
112 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("RobExtremes")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for RobExtremes version 1.3.2 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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