LSEbootLS: Bootstrap Methods for Regression Models with Locally Stationary Errors

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

Documentation:

Reference manual:

LSEbootLS.html , LSEbootLS.pdf

Downloads:

Package source:	LSEbootLS_0.1.0.tar.gz
Windows binaries:	r-devel: LSEbootLS_0.1.0.zip, 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

Linking:

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