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.
| Version: |
0.2.8 |
| Depends: |
R (≥ 2.15.3) |
| Imports: |
Matrix |
| Published: |
2023-06-29 |
| DOI: |
10.32614/CRAN.package.dbacf |
| Author: |
Inder Tecuapetla-Gómez [aut, cre] |
| Maintainer: |
Inder Tecuapetla-Gómez
<itecuapetla at conabio.gob.mx> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
dbacf results |
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