Score-driven filters

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papersSEP 10 04:00 UTC

Online Learning of Scale Parameters in Score-Driven Filters

A new research paper addresses how to learn the gain, the scale parameter that multiplies the scaled log-likelihood score in score-driven filters, directly online. Rather than fixing this coefficient beforehand, the method treats each admissible gain as selecting a reachable next state given the current state and the realized scaled score. This allows the filter's update step to adapt during operation.

time-series/online-learning/filtering