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- W3134597412 abstract "Abstract We examine the large sample behavior of Bayesian posterior distributions in a nonlinear regression model for statistical inference in distributed parameter identification. Under suitable conditions, we prove the consistency of the parameter identification algorithm via Bayesian approach. We then derive large deviations results for independent, identically distributed error models. The large deviations ascertain the rate of convergence. We show that the convergence mentioned above is exponentially fast. That is, there exists a nonnegative function I defined on the parameter set such that πn(dq) ∼ exp(−nI(q))dp for almost all ω, where πn is the conditional distribution of the parameter, given the observations." @default.
- W3134597412 created "2021-03-15" @default.
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- W3134597412 date "1995-09-17" @default.
- W3134597412 modified "2023-10-16" @default.
- W3134597412 title "Convergence and Large Deviations in a Bayesian Approach to Functional Estimation Problems" @default.
- W3134597412 doi "https://doi.org/10.1115/detc1995-0670" @default.
- W3134597412 hasPublicationYear "1995" @default.
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