Maxima Units Search (MUS) Algorithm: Methodology and Applications

Autor:	Roberta Pappadà, Leonardo Egidi, Nicola Torelli, Francesco Pauli
Přispěvatelé:	Cira Perna, Monica Pratesi, Anne Ruiz-Gazen, Egidi, Leonardo, Pappada', Roberta, Pauli, Francesco, Torelli, Nicola
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	Computer science Bayesian probability Rank (computer programming) Identity matrix Block matrix Label switching Mixture model Pivotal unit Maxima Algorithm Sparse matrix
Zdroj:	Springer Proceedings in Mathematics & Statistics ISBN: 9783319739052
DOI:	10.1007/978-3-319-73906-9_7
Popis:	An algorithm for extracting identity submatrices of small rank and pivotal units from large and sparse matrices is proposed. The procedure has already been satisfactorily applied for solving the label switching problem in Bayesian mixture models. Here we introduce it on its own and explore possible applications in different contexts.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::530abab9797eca826e49efa0914bcebb https://link.springer.com/chapter/10.1007/978-3-319-73906-9_7 Zobrazit plný text záznamu