Minimum information dependence modeling

被引：0

作者：

Sei, Tomonari ^{[1
]}

Yano, Keisuke ^{[2
]}

机构：

[1] Univ Tokyo, 7-3-1 Hongo,Bunkyo Ku, Tokyo 1138656, Japan

[2] Inst Stat Math, 10-3 Midori Cho, Tachikawa, Tokyo 1908562, Japan

来源：

BERNOULLI | 2024年 / 30卷 / 04期

关键词：

Conditional inference; copula; earthquake data; graphical model; mixed-domain; Monte Carlo method; EXPONENTIAL-FAMILIES; MAXIMUM-LIKELIHOOD; OPTIMAL TRANSPORT; GEOMETRY; DISTRIBUTIONS; MINIMIZATION; COPULAS;

D O I：

10.3150/23-BEJ1687

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：

We propose a method to construct a joint statistical model for mixed-domain data to analyze their dependence. Multivariate Gaussian and log-linear models are particular examples of the proposed model. It is shown that the functional equation defining the model has a unique solution under fairly weak conditions. The model is characterized by two orthogonal parameters: the dependence parameter and the marginal parameter. To estimate the dependence parameter, a conditional inference together with a sampling procedure is proposed and is shown to provide a consistent estimator. Illustrative examples of data analyses involving penguins and earthquakes are presented.

引用

页码：2623 / 2643

页数：21

共 53 条

[1] Finite-Sample Concentration of the Multinomial in Relative Entropy [J].

Agrawal, Rohit .

IEEE TRANSACTIONS ON INFORMATION THEORY, 2020, 66 (10) :6297-6302

[2]

ALBERT A, 1984, BIOMETRIKA, V71, P1

[3] Information geometry on hierarchy of probability distributions [J].

Amari, S .

IEEE TRANSACTIONS ON INFORMATION THEORY, 2001, 47 (05) :1701-1711

[4]

[Anonymous], 2000, Methods of Information Geometry. Translations of Mathematical Monographs, DOI DOI 10.1090/MMONO/191

[5]

[Anonymous], 1996, Graphical Models. Oxford Statistical Science Series

[6] Approximate Uncertainty Modeling in Risk Analysis with Vine Copulas [J].

Bedford, Tim ;

Daneshkhah, Alireza ;

Wilson, Kevin J. .

RISK ANALYSIS, 2016, 36 (04) :792-815

[7] On the construction of minimum information bivariate copula families [J].

Bedford, Tim ;

Wilson, Kevin J. .

ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 2014, 66 (04) :703-723

[8] ENTROPY MINIMIZATION, DAD PROBLEMS, AND DOUBLY STOCHASTIC KERNELS [J].

BORWEIN, JM ;

LEWIS, AS ;

NUSSBAUM, RD .

JOURNAL OF FUNCTIONAL ANALYSIS, 1994, 123 (02) :264-307

[9]

Bose A., 2018, Texts and Readings in Mathematics, V75, DOI [10.1007/978-981-13-2248-8, DOI 10.1007/978-981-13-2248-8]

[10]

BUJA A, 1989, ANN STAT, V17, P453, DOI 10.1214/aos/1176347115

← 1 2 3 4 5 6 →