<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Linearly structured covariance matrices are widely used in multivariate analysis. The covariance structure can be chosen from a class of linear structures. Therefore, the optimal structure is identified in terms of minimizing the discrepancy function. In this research, the entropy loss function is used as the discrepancy function. We give a methodology and algorithm for determining the optimal structure from the class of structures under consideration. The accuracy of the proposed method is checked using a simulation study.</p>
</abstract>

Linearly structured covariance matrices are widely used in multivariate analysis. The covariance structure can be chosen from a class of linear structures. Therefore, the optimal structure is identified in terms of minimizing the discrepancy function. In this research, the entropy loss function is used as the discrepancy function. We give a methodology and algorithm for determining the optimal structure from the class of structures under consideration. The accuracy of the proposed method is checked using a simulation study.

Structure identification for a linearly structured covariance matrix

Department of Mathematical and Statistical Methods

Biometrical Letters

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Structure identification for a linearly structured covariance matrix"}

Linearly structured covariance matrices are widely used in multivariate analysis. The covariance structure can be chosen from a class of linear structures....

Structure identification for a linearly structured covariance matrix

Online veröffentlicht: 30. Dez. 2022

Seitenbereich: 159 - 169

DOI: https://doi.org/10.2478/bile-2022-0011

Schlüsselwörter
covariance structure, compound symmetry matrix, banded Toeplitz matrix, identification, entropy loss function

© 2022 Adam Mieldzioc, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Structure identification for a linearly structured covariance matrix

Online veröffentlicht: 30. Dez. 2022

Seitenbereich: 159 - 169

DOI: https://doi.org/10.2478/bile-2022-0011

Schlüsselwörtercovariance structure, compound symmetry matrix, banded Toeplitz matrix, identification, entropy loss function

© 2022 Adam Mieldzioc, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
covariance structure, compound symmetry matrix, banded Toeplitz matrix, identification, entropy loss function