This paper focuses on studying the relationships among a set of categorical (ordinal) variables collected in a contingency table. Besides the marginal and conditional (in)dependencies, thoroughly analyzed in the literature, we consider the context-specific independencies holding only in a subspace of the outcome space of the conditioning variables. To this purpose we consider the Hierarchical Multinomial Marginal models and we provide several original results about the representation of context-specific independencies through these models. The theoretical results are supported by an application concerning the innovation degree of Italian enterprises.

Context-specific independencies in Hierarchical Multinomial Marginal models / F. Nicolussi, M. Cazzaro. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - (2019 Dec 05). [Epub ahead of print] [10.1007/s10260-019-00503-8]

Context-specific independencies in Hierarchical Multinomial Marginal models

F. Nicolussi;
2019-12-05

Abstract

This paper focuses on studying the relationships among a set of categorical (ordinal) variables collected in a contingency table. Besides the marginal and conditional (in)dependencies, thoroughly analyzed in the literature, we consider the context-specific independencies holding only in a subspace of the outcome space of the conditioning variables. To this purpose we consider the Hierarchical Multinomial Marginal models and we provide several original results about the representation of context-specific independencies through these models. The theoretical results are supported by an application concerning the innovation degree of Italian enterprises.
Context-specific independence; Ordinal variable; Hierarchical Multinomial Marginal model
Settore SECS-S/01 - Statistica
STATISTICAL METHODS & APPLICATIONS
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/694931
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