evmissing: Extreme Value Analyses with Missing Data
Performs likelihood-based extreme value inferences with
adjustment for the presence of missing values based on Simpson and
Northrop (2025) <doi:10.48550/arXiv.2512.15429>. A Generalised Extreme Value
distribution is fitted to block maxima using maximum likelihood estimation,
with the location and scale parameters reflecting the numbers of
non-missing raw values in each block. A Bayesian version is also provided.
For the purposes of comparison, there are options to make no adjustment for
missing values or to discard any block maximum for which greater than a
percentage of the underlying raw values are missing. Example datasets
containing missing values are provided.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
gamlssx, graphics, itp, nieve, revdbayes, rust, stats |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2026-01-08 |
| DOI: |
10.32614/CRAN.package.evmissing (may not be active yet) |
| Author: |
Paul J. Northrop [aut, cre, cph],
Emma S. Simpson [aut, cph] |
| Maintainer: |
Paul J. Northrop <p.northrop at ucl.ac.uk> |
| BugReports: |
https://github.com/paulnorthrop/evmissing/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://paulnorthrop.github.io/evmissing/,
https://github.com/paulnorthrop/evmissing |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
evmissing results |
Documentation:
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