lite
Likelihood-Based Inference for Time Series Extremes
Performs likelihood-based inference for stationary time series extremes. The general approach follows Fawcett and Walshaw (2012) <doi:10.1002/env.2133>. Marginal extreme value inferences are adjusted for cluster dependence in the data using the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, producing an adjusted log-likelihood for the model parameters. A log-likelihood for the extremal index is produced using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. These log-likelihoods are combined to make inferences about extreme values. Both maximum likelihood and Bayesian approaches are available.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.1 |
rolling linux/jammy R-4.5 | lite_1.1.1.tar.gz |
247.6 KiB |
1.1.1 |
rolling linux/noble R-4.5 | lite_1.1.1.tar.gz |
247.6 KiB |
1.1.1 |
rolling source/ R- | lite_1.1.1.tar.gz |
118.8 KiB |
1.1.1 |
latest linux/jammy R-4.5 | lite_1.1.1.tar.gz |
247.6 KiB |
1.1.1 |
latest linux/noble R-4.5 | lite_1.1.1.tar.gz |
247.6 KiB |
1.1.1 |
latest source/ R- | lite_1.1.1.tar.gz |
118.8 KiB |
1.1.1 |
2026-04-26 source/ R- | lite_1.1.1.tar.gz |
118.8 KiB |
1.1.1 |
2026-04-23 source/ R- | lite_1.1.1.tar.gz |
118.8 KiB |
1.1.1 |
2026-04-09 windows/windows R-4.5 | lite_1.1.1.zip |
249.3 KiB |
1.1.1 |
2025-04-20 source/ R- | lite_1.1.1.tar.gz |
118.8 KiB |