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Please use this identifier to cite or link to this item: http://hdl.handle.net/2307/3791

Title: Structural learning of bayesian networks from ordinal data
Authors: Musella, Flaminia
Tutor: Vicard, Paola
Issue Date: 28-Mar-2011
Publisher: Universit√† degli studi Roma Tre
Abstract: In observational studies many features are measured on a sample in a given time. When the measurement scale is ordinal, observed variables are categorical ordinal variables. Their increasing presence in databases has in uenced the development of methods for ordinal data analysis (Joe 1971; Clogg and Shihadeh 1994; Agresti 2010). Frequently, researchers are interested in the multivariate analysis and dependencies (Cox and Wermuth 1996). Graphical models (Lauritzen 1996) can be useful for this
URI: http://hdl.handle.net/2307/3791
Access Rights: info:eu-repo/semantics/openAccess
Appears in Collections:Dipartimento di Economia
T - Tesi di dottorato

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