Expectation propagation for the smoothing distribution in dynamic probit

• URL: http://arxiv.org/abs/2309.01641v1
• Date: Mon, 4 Sep 2023 14:49:45 GMT
• Title: Expectation propagation for the smoothing distribution in dynamic probit
• Authors: Niccol\`o Anceschi, Augusto Fasano, Giovanni Rebaudo
• Abstract summary: The smoothing distribution of dynamic probit models with Gaussian state dynamics was recently proved to belong to the unified skew-normal family. We derive an efficient EP routine to perform inference for such a distribution. We show that the proposed approximation leads to accuracy gains over available approximate algorithms in a financial illustration.
• Score: 1.6114012813668932
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The smoothing distribution of dynamic probit models with Gaussian state dynamics was recently proved to belong to the unified skew-normal family. Although this is computationally tractable in small-to-moderate settings, it may become computationally impractical in higher dimensions. In this work, adapting a recent more general class of expectation propagation (EP) algorithms, we derive an efficient EP routine to perform inference for such a distribution. We show that the proposed approximation leads to accuracy gains over available approximate algorithms in a financial illustration.

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