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MODEL SELECTION FOR LOG-LINEAR MODELS OF contingency tables

Journal of Systems Science & Complexity 2003年第2期16卷 249-259页

作者： ZHAO Lincheng ZHANG Hong(University of Science and Technology of China, Hefei, Anhui 230026. China) University of Science and Technology of China 安徽 Hefei 230026

In this paper, we propose an information-theoretic-criterion-based modelselection procedure for log-linear model of contingency tables under multinomial sampling, andestablish the strong consistency of the method under some mild conditions. An exponential bound ofmiss detection probability is also obtained. The selection procedure is modified so that it can beused in practice. Simulation shows that the modified method is valid. To avoid selecting the penaltycoefficient in the information criteria, an alternative selection procedure is given.

关键词： contingency tables log-linear model model selection strong consistency exponential bound

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Confidence Intervals for Relative Intensity of Collaboration(RIC)Indicators

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Journal of Data and Information Science 2022年第4期7卷 5-15页

作者： Joel Emanuel Fuchs Lawrence Smolinsky Ronald Rousseau University of Wuppertal Gaußstr.20D-42119 WuppertalGermany Louisiana State University Department of MathematicsBaton RougeLos AngelesUSA University of Antwerp Faculty of Social SciencesMiddelheimlaan 1B-2020 AntwerpBelgium KU Leuven Facultair Onderzoekscentrum ECOOMNaamsestraat 61B-3000 LeuvenBelgium

Purpose:We aim to extend our investigations related to the Relative Intensity of Collaboration(RIC)indicator,by constructing a confidence interval for the obtained ***/methodology/approach:We use Mantel-Haenszel statistics as applied recently by Smolinsky,Klingenberg,and ***:We obtain confidence intervals for the RIC indicatorResearch limitations:It is not obvious that data obtained from the Web of Science(or any other database)can be considered a random *** implications:We explain how to calculate confidence *** indicators are more often than not presented as precise values instead of an approximation depending on the database and the time of *** approach presents a suggestion to solve this ***/value:Our approach combines the statistics of binary categorical data and bibliometric studies of collaboration.

关键词： contingency tables Confidence intervals Relative intensity of collaboration(RIC) Mantel-Haenszel statistics Science of science

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Decomposition of Covariate-Dependent Graphical Models with Categorical Data

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Communications in Mathematical Research 2023年第3期39卷 414-436页

作者： Binghui Liu Jianhua Guo School of Mathematics and Statistics&KLAS Northeast Normal UniversityChangchunJilin 130024P.R.China

Graphical models are wildly used to describe conditional dependence relationships among interacting random *** statistical inference problems of a graphical model,one particular interest is utilizing its interaction structure to reduce model *** an important approach to utilizing structural information,decomposition allows a statistical inference problem to be divided into some sub-problems with lower *** this paper,to investigate decomposition of covariate-dependent graphical models,we propose some useful definitions of decomposition of covariate-dependent graphical models with categorical data in the form of contingency *** on such a decomposition,a covariate-dependent graphical model can be split into some sub-models,and the maximum likelihood estimation of this model can be factorized into the maximum likelihood estimations of the ***,some sufficient and necessary conditions of the proposed definitions of decomposition are studied.

关键词： Collapsibility contingency tables covariate-dependent decomposition graphical models

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