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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.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 LSEbootLS_0.1.0.tar.gz 127.3 KiB
0.1.0 rolling linux/noble R-4.5 LSEbootLS_0.1.0.tar.gz 127.2 KiB
0.1.0 rolling source/ R- LSEbootLS_0.1.0.tar.gz 18.2 KiB
0.1.0 latest linux/jammy R-4.5 LSEbootLS_0.1.0.tar.gz 127.3 KiB
0.1.0 latest linux/noble R-4.5 LSEbootLS_0.1.0.tar.gz 127.2 KiB
0.1.0 latest source/ R- LSEbootLS_0.1.0.tar.gz 18.2 KiB
0.1.0 2026-04-26 source/ R- LSEbootLS_0.1.0.tar.gz 18.2 KiB
0.1.0 2026-04-23 source/ R- LSEbootLS_0.1.0.tar.gz 18.2 KiB
0.1.0 2026-04-09 windows/windows R-4.5 LSEbootLS_0.1.0.zip 130.9 KiB
0.1.0 2025-04-20 source/ R- LSEbootLS_0.1.0.tar.gz 18.2 KiB

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