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

Japanese Journal of Statistics and Data Science, ISSN: 2520-8764
2024
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Article Description

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.

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