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.File | Dimensione | Formato | |
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