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LSEbootLS  

Bootstrap Methods for Regression Models with Locally Stationary Errors
View on CRAN: Click here


Download and install LSEbootLS package within the R console
Install from CRAN:
install.packages("LSEbootLS")

Install from Github:
library("remotes")
install_github("cran/LSEbootLS")

Install by package version:
library("remotes")
install_version("LSEbootLS", "0.1.0")



Attach the package and use:
library("LSEbootLS")
Maintained by
Nicolas Loyola
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-07-01
Latest Update: 2024-07-01
Description:
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.
How to cite:
Nicolas Loyola (2024). LSEbootLS: Bootstrap Methods for Regression Models with Locally Stationary Errors. R package version 0.1.0, https://cran.r-project.org/web/packages/LSEbootLS. Accessed 21 Nov. 2024.
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