Bootstrap Methods for Regression Models with Locally Stationary Errors R package LSEbootLS version 0.1.0 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. Software Depends: doParallel, R (>= 2.10) Imports: foreach, doRNG, stats, parallel, LSTS, tibble, iterators, rlecuyer Suggests: testthat (>= 3.0.0) Nicolas Loyola <nloyola2016@udec.cl> Comprehensive R Archive Network (CRAN) Guillermo Ferreira [aut], Joel Muñoz [aut], Nicolas Loyola [aut, cre] GPL (>= 3) 2024-07-01 application/tgz https://CRAN.R-project.org/package=LSEbootLS doi:10.32614/CRAN.package.LSEbootLS