Context-specific independencies in hierarchical multinomial marginal models

被引：2
|
作者：
Nicolussi, Federica [1 ]
Cazzaro, Manuela [2 ]
机构：
[1] Univ Milan, Dept Econ Management & Quantitat Methods, Milan, Italy
[2] Univ Milano Bicocca, Dept Stat & Quantitat Methods, Milan, Italy
来源：
STATISTICAL METHODS AND APPLICATIONS | 2020年 / 29卷 / 04期
关键词：
Context-specific independence; Ordinal variable; Hierarchical multinomial marginal model; CONTINGENCY-TABLES; GRAPHICAL MODELS;
D O I：
10.1007/s10260-019-00503-8
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
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.
引用
收藏
页码：767 / 786
页数：20
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