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Implements bootstrap methods for linear regression models with errors following a time-varying process, focusing on approximating the distribution of the least-squares estimator for regression models with locally stationary errors. It enables the construction of bootstrap and classical confidence intervals for regression coefficients, leveraging intensive simulation studies and real data analysis.
| Version: | 0.1.0 |
| Depends: | doParallel, R (≥ 2.10) |
| Imports: | foreach, doRNG, stats, parallel, LSTS, tibble, iterators, rlecuyer |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2024-07-01 |
| DOI: | 10.32614/CRAN.package.LSEbootLS |
| Author: | Guillermo Ferreira [aut], Joel Muñoz [aut], Nicolas Loyola [aut, cre] |
| Maintainer: | Nicolas Loyola <nloyola2016 at udec.cl> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Citation: | LSEbootLS citation info |
| CRAN checks: | LSEbootLS results |
| Reference manual: | LSEbootLS.pdf |
| Package source: | LSEbootLS_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: LSEbootLS_0.1.0.zip, r-oldrel: LSEbootLS_0.1.0.zip |
| macOS binaries: | r-release (arm64): LSEbootLS_0.1.0.tgz, r-oldrel (arm64): LSEbootLS_0.1.0.tgz, r-release (x86_64): LSEbootLS_0.1.0.tgz, r-oldrel (x86_64): LSEbootLS_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.