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dbacf

Autocovariance Estimation via Difference-Based Methods

Provides methods for (auto)covariance/correlation function estimation in change point regression with stationary errors circumventing the pre-estimation of the underlying signal of the observations. Generic, first-order, (m+1)-gapped, difference-based autocovariance function estimator is based on M. Levine and I. Tecuapetla-Gómez (2023) <doi:10.48550/arXiv.1905.04578>. Bias-reducing, second-order, (m+1)-gapped, difference-based estimator is based on I. Tecuapetla-Gómez and A. Munk (2017) <doi:10.1111/sjos.12256>. Robust autocovariance estimator for change point regression with autoregressive errors is based on S. Chakar et al. (2017) <doi:10.3150/15-BEJ782>. It also includes a general projection-based method for covariance matrix estimation.

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VersionRepositoryFileSize
0.2.8 rolling linux/jammy R-4.5 dbacf_0.2.8.tar.gz 47.6 KiB
0.2.8 rolling linux/noble R-4.5 dbacf_0.2.8.tar.gz 47.6 KiB
0.2.8 rolling source/ R- dbacf_0.2.8.tar.gz 11.1 KiB
0.2.8 latest linux/jammy R-4.5 dbacf_0.2.8.tar.gz 47.6 KiB
0.2.8 latest linux/noble R-4.5 dbacf_0.2.8.tar.gz 47.6 KiB
0.2.8 latest source/ R- dbacf_0.2.8.tar.gz 11.1 KiB
0.2.8 2026-04-26 source/ R- dbacf_0.2.8.tar.gz 11.1 KiB
0.2.8 2026-04-23 source/ R- dbacf_0.2.8.tar.gz 11.1 KiB
0.2.8 2026-04-09 windows/windows R-4.5 dbacf_0.2.8.zip 50.2 KiB
0.2.8 2025-04-20 source/ R- dbacf_0.2.8.tar.gz 11.1 KiB

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