QBIC of SEM for jump-diffusion processes based on high-frequency data
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866915936050610176 |
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| author | Kusano, Shogo Uchida, Masayuki |
| author_facet | Kusano, Shogo Uchida, Masayuki |
| contents | Structural equation modeling (SEM) is a statistical method for analyzing relationships among latent variables. Since SEM is a confirmatory method, the model needs to be specified in advance. In practice, however, statisticians have several candidate models and aim to select the most appropriate one among them. In this paper, we consider model selection in SEM for jump-diffusion processes. We propose a quasi-Bayesian information criterion (QBIC) for the SEM and show that the proposed criterion has model-selection consistency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_12093 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | QBIC of SEM for jump-diffusion processes based on high-frequency data Kusano, Shogo Uchida, Masayuki Statistics Theory Structural equation modeling (SEM) is a statistical method for analyzing relationships among latent variables. Since SEM is a confirmatory method, the model needs to be specified in advance. In practice, however, statisticians have several candidate models and aim to select the most appropriate one among them. In this paper, we consider model selection in SEM for jump-diffusion processes. We propose a quasi-Bayesian information criterion (QBIC) for the SEM and show that the proposed criterion has model-selection consistency. |
| title | QBIC of SEM for jump-diffusion processes based on high-frequency data |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2604.12093 |