Predictive information criterion for jump diffusion processes

2025/08/01 by Uehara, Yuma
#FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.2508.00411

Abstract

In this paper, we address a model selection problem for ergodic jump diffusion processes based on high-frequency samples. We evaluate the expected genuine log-likelihood function and derive an Akaike-type information criterion based on the threshold-based quasi-likelihood function. In the derivation process, we also give new estimates of the transition density of jump diffusion processes. We also provide the relative selection probability of the proposed information criterion.

Citations

• Gaussian quasi-information criteria for ergodic Lévy driven SDE
• Density estimates for jump diffusion processes
• Invariant density adaptive estimation for ergodic jump diffusion processes over anisotropic classes
• Schwartz type model selection for ergodic stochastic differential equation models
• Heat kernels for non-symmetric diffusion operators with jumps
• Schwarz type model comparison for LAQ models
• LAN property for an ergodic diffusion with jumps
• Information Criteria for Multivariate CARMA Processes

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