smoothtail
Smooth Estimation of GPD Shape Parameter
Given independent and identically distributed observations X(1), ..., X(n) from a Generalized Pareto distribution with shape parameter gamma in [-1,0], offers several estimates to compute estimates of gamma. The estimates are based on the principle of replacing the order statistics by quantiles of a distribution function based on a log--concave density function. This procedure is justified by the fact that the GPD density is log--concave for gamma in [-1,0].
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.6 |
rolling linux/jammy R-4.5 | smoothtail_2.0.6.tar.gz |
50.8 KiB |
2.0.6 |
rolling linux/noble R-4.5 | smoothtail_2.0.6.tar.gz |
50.8 KiB |
2.0.6 |
rolling source/ R- | smoothtail_2.0.6.tar.gz |
8.5 KiB |
2.0.6 |
latest linux/jammy R-4.5 | smoothtail_2.0.6.tar.gz |
50.8 KiB |
2.0.6 |
latest linux/noble R-4.5 | smoothtail_2.0.6.tar.gz |
50.8 KiB |
2.0.6 |
latest source/ R- | smoothtail_2.0.6.tar.gz |
8.5 KiB |
2.0.6 |
2026-04-26 source/ R- | smoothtail_2.0.6.tar.gz |
8.5 KiB |
2.0.6 |
2026-04-23 source/ R- | smoothtail_2.0.6.tar.gz |
8.5 KiB |
2.0.6 |
2026-04-09 windows/windows R-4.5 | smoothtail_2.0.6.zip |
53.8 KiB |
2.0.6 |
2025-04-20 source/ R- | smoothtail_2.0.6.tar.gz |
8.5 KiB |
Dependencies (latest)
Depends
- logcondens (>= 2.0.0)