Papers › Expectation propagation for the smoothing distribution in dynamic probit
Expectation propagation for the smoothing distribution in dynamic probit
Niccolò Anceschi, Augusto Fasano, Giovanni Rebaudo
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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