Package: tea 1.1
Johannes Ossberger
tea: Threshold Estimation Approaches
Different approaches for selecting the threshold in generalized Pareto distributions. Most of them are based on minimizing the AMSE-criterion or at least by reducing the bias of the assumed GPD-model. Others are heuristically motivated by searching for stable sample paths, i.e. a nearly constant region of the tail index estimator with respect to k, which is the number of data in the tail. The third class is motivated by graphical inspection. In addition, a sequential testing procedure for GPD-GoF-tests is also implemented here.
Authors:
tea_1.1.tar.gz
tea_1.1.tar.gz(r-4.5-noble)tea_1.1.tar.gz(r-4.4-noble)
tea_1.1.tgz(r-4.4-emscripten)tea_1.1.tgz(r-4.3-emscripten)
tea.pdf |tea.html✨
tea/json (API)
| # Install 'tea' in R: |
| install.packages('tea', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:d0fb4bd084. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
Exports:althillavhilldAMSEdanielssondgpdDKeyeggplotGHgomesgpdFithallHimpHWmindistpgpdPSqgpdqqestplotqqgpdrgpdRTsumplotTH
