Extreme Value Analyses with Missing Data
Overview
Performs likelihood-based extreme value inferences with adjustment for the presence of missing values based on Simpson and Northrop (2026) doi:10.1002/env.70075. 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.
- Simpson and Northrop (2006) has appeared in Environmetrics 37(2).
From NEWS.md in the release
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- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 22 (1 internal)includes a package overview page
- Examples that run
- 100%18 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 80%
- Return-value docs
- 100%
- Help pages citing references
- 32%
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Package metadata
- First published
- 2026-01-08
- Total releases
- 3 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 44 KB / 7 files
- Download size
- 154 KB
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