Exécution de notre outil de synthèse sur un nouvel article
Vérifiez l’article ci-dessous, puis lancez sa synthèse.
Structure identification for a linearly structured covariance matrix
Adam Mieldzioc (Poznań University of Life Sciences)
Biometrical Letters
DOI: 10.2478/bile-2022-0011 (Mathematics)
Licence : CC BY-NC-ND
Résumé : Summary 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.
Publié le 01 Déc. 2022