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Strong Consistency of Bayes Estimates in Stochastic Regression Models

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  • Hu, Inchi

Abstract

Under minimum assumptions on the stochastic regressors, strong consistency of Bayes estimates is established in stochastic regression models in two cases: (1) When the prior distribution is discrete, the p.d.f.fof i.i.d. random errors is assumed to have finite Fisher informationI=[integral operator][infinity]-[infinity](f')2/f dx

Suggested Citation

  • Hu, Inchi, 1996. "Strong Consistency of Bayes Estimates in Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 57(2), pages 215-227, May.
    • Handle: RePEc:eee:jmvana:v:57:y:1996:i:2:p:215-227
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    Cited by:

    1. Luc Pronzato & Éric Thierry, 2002. "Sequential experimental design and response optimisation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 277-292, October.
    2. Arnoud V. den Boer & Bert Zwart, 2015. "Dynamic Pricing and Learning with Finite Inventories," Operations Research, INFORMS, vol. 63(4), pages 965-978, August.

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