Finite-sample complexity of sequential Monte Carlo estimators

We present bounds for the finite-sample error of sequential Monte Carlo samplers on static spaces. Our approach explicitly relates the performance of the algorithm to properties of the chosen sequence of distributions and mixing properties of the associated Markov kernels. This allows us to give the...

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Veröffentlicht in:	The Annals of statistics 2023-06, Vol.51 (3), p.1357
Hauptverfasser:	Marion, Joe, Mathews, Joseph, Schmidler, Scott C.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Complexity Finite element analysis Markov analysis Markov chains Mechanical properties Monte Carlo simulation Sampling error Statistics
Online-Zugang:	Volltext
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