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Maximum likelihood recursive state estimation in state-space models: A new approach based on statistical analysis of incomplete data. (arXiv:2211.04631v1 [stat.ME])
stat.ML updates on arXiv.org arxiv.org
This paper revisits the work of Rauch et al. (1965) and develops a novel
method for recursive maximum likelihood particle filtering for general
state-space models. The new method is based on statistical analysis of
incomplete observations of the systems. Score function and conditional observed
information of the incomplete observations/data are introduced and their
distributional properties are discussed. Some identities concerning the score
function and information matrices of the incomplete data are derived. Maximum
likelihood estimation of state-vector is presented in …
analysis arxiv data incomplete data likelihood recursive space state statistical