Quasi-Akaike information criterion of SEM with latent variables for diffusion processes

被引：0

作者：

Kusano, Shogo ^{[1
]}

Uchida, Masayuki ^{[1
,2
,3
]}

机构：

[1] Osaka Univ, Grad Sch Engn Sci, Toyonaka, Japan

[2] Osaka Univ, Ctr Math Modeling & Data Sci MMDS, Toyonaka, Japan

[3] Japan Sci & Technol Agcy, CREST, Tokyo, Japan

来源：

JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE | 2024年

关键词：

Structural equation modeling; Quasi-Akaike information criterion; Quasi-likelihood analysis; High-frequency data; Stochastic differential equation;

D O I：

10.1007/s42081-024-00271-0

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 consider a model selection problem for structural equation modeling (SEM) with latent variables for diffusion processes based on high-frequency data. First, we propose the quasi-Akaike information criterion of the SEM and study the asymptotic properties. Next, we consider the situation where the set of competing models includes some misspecified parametric models. It is shown that the probability of choosing the misspecified models converges to zero. Furthermore, examples and simulation results are given.

引用

页数：48