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