Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference
نویسندگان
چکیده
منابع مشابه
Central Limit Theorem for Sequential Monte Carlo Methods and Its Application to Bayesian Inference
The term “sequential Monte Carlo methods” or, equivalently, “particle filters,” refers to a general class of iterative algorithms that performs Monte Carlo approximations of a given sequence of distributions of interest (πt). We establish in this paper a central limit theorem for the Monte Carlo estimates produced by these computational methods. This result holds under minimal assumptions on th...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2004
ISSN: 0090-5364
DOI: 10.1214/009053604000000698