Algebraic statistics in practice: applications to networks
Visualitza/Obre
10.1146/annurev-statistics-031017-100053
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/344004
Tipus de documentArticle
Data publicació2020-01-01
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
Algebraic statistics uses tools from algebra (especially from multilinear algebra, commutative algebra, and computational algebra), geometry, and combinatorics to provide insight into knotty problems in mathematical statistics. In this review, we illustrate this on three problems related to networks: network models for relational data, causal structure discovery, and phylogenetics. For each problem, we give an overview of recent results in algebraic statistics, with emphasis on the statistical achievements made possible by these tools and their practical relevance for applications to other scientific disciplines.
CitacióCasanellas, M.; Petrovic, S.; Uhler, C. Algebraic statistics in practice: applications to networks. "Annual Review of Statistics and Its Application", 1 Gener 2020, vol. 7, p. 227-250.
ISSN2326-8298
Altres identificadorshttps://arxiv.org/abs/1906.09537
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ARSIA_arxiv1906.09537.pdf | 3,595Mb | Visualitza/Obre |