Advances in Approximate Bayesian Computation and Trans-Dimensional Sampling Methodology
نویسندگان
چکیده
منابع مشابه
Approximate Bayesian Computation Estimator for Respondent-Driven Sampling
Respondent-driven sampling is a network-based technique to collect information and make estimation about behavior and composition of social groups in hidden population. The non-randomly selected samples prohibit the use of the sample mean as a statistically valid estimator. Researchers have proposed several asymptotically unbiased estimators, but many fail to realize that the high variance of t...
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Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices amon...
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For many complex probability models, computation of likelihoods is either impossible or very time consuming. In this article, we discuss methods for simulating observations from posterior distributions without the use of likelihoods. A rejection approach is illustrated using an example concerning inference in the fossil record. A novel Markov chain Monte Carlo approach is also described, and il...
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ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2009
ISSN: 1556-5068
DOI: 10.2139/ssrn.3785580