Package: EncompassTest 0.22
Rong Peng
EncompassTest: Direct Multi-Step Forecast Based Comparison of Nested Models via an Encompassing Test
The encompassing test is developed based on multi-step-ahead predictions of two nested models as in Pitarakis, J. (2023) <doi:10.48550/arXiv.2312.16099>. The statistics are standardised to a normal distribution, and the null hypothesis is that the larger model contains no additional useful information. P-values will be provided in the output.
Authors:
EncompassTest_0.22.tar.gz
EncompassTest_0.22.tar.gz(r-4.7-any)EncompassTest_0.22.tar.gz(r-4.6-any)
EncompassTest_0.22.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
EncompassTest/json (API)
| # Install 'EncompassTest' in R: |
| install.packages('EncompassTest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:24a457ffb9. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 96 | ||
| source / vignettes | OK | 167 | ||
| linux-release-x86_64 | OK | 104 | ||
| wasm-release | OK | 93 |
Exports:andrews_lrvNW_lrvpred_encompass_dnormrecursive_hstep_fast
Dependencies:pracma
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Long-run covariance estimation using Andrews quadratic spectral kernel. | andrews_lrv |
| Long-run covariance estimation using Newey-West (Bartlett) weights | NW_lrv |
| Direct Multi-Step Forecast Based Comparison of Nested Models via an Encompassing Test | pred_encompass_dnorm |
| Forecasting h-steps ahead using Recursive Least Squares Fast | recursive_hstep_fast |