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Title:

Structure Learning in Graphical Modeling

Document type:
Zeitschriftenaufsatz
Author(s):
Drton, Mathias and Maathuis, Marloes H.
Abstract:
A graphical model is a statistical model that is associated with a graph whose nodes correspond to variables of interest. The edges of the graph reflect allowed conditional dependencies among the variables. Graphical models have computationally convenient factorization properties and have long been a valuable tool for tractable modeling of multivariate distributions. More recently, applications such as reconstructing gene regulatory networks from gene expression data have driven major advances i...     »
Keywords:
Bayesian network, graphical model, Markov random field, model selection, multivariate statistics, network reconstruction
Dewey Decimal Classification:
510 Mathematik
Journal title:
Annual Review of Statistics and Its Application
Year:
2017
Journal volume:
4
Year / month:
2017-03
Quarter:
1. Quartal
Month:
Mar
Journal issue:
1
Pages contribution:
365-393
Language:
en
Fulltext / DOI:
doi:10.1146/annurev-statistics-060116-053803
Publisher:
Annual Reviews
E-ISSN:
2326-82982326-831X
Date of publication:
07.03.2017
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