projectToeplitz

Computes the orthogonal projection onto the space of symmetric Toeplitz 
matrices as given in <cite>Grigoriadis et al. (1994)</cite>.

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.

Inder Tecuapetla-G<c3><b3>mez

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Autocovariance Estimation via Difference-Based Methods

Inder Tecuapetla-Gómez

projectToeplitz function

<dl><dt>matrix</dt>
<dd>a symmetric matrix.</dd></dl>

Arguments

Projection onto the set of symmetric Toeplitz matrices — projectToeplitz

<dl>

<dt>matrix</dt>
<dd>a symmetric matrix.</dd>

</dl>

projectToeplitz: Projection onto the set of symmetric Toeplitz matrices

Description

Usage

Value

Arguments

References

See Also

Examples