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Asymptotic properties of nonlinear estimates in stochastic models with finite design space

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  • Pronzato, Luc

Abstract

Under the condition that the design space is finite, new sufficient conditions for the strong consistency and asymptotic normality of the least-squares estimator in nonlinear stochastic regression models are derived. Similar conditions are obtained for the maximum-likelihood estimator in Bernoulli-type experiments. Consequences on the sequential design of experiments are pointed out.

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  • Pronzato, Luc, 2009. "Asymptotic properties of nonlinear estimates in stochastic models with finite design space," Statistics & Probability Letters, Elsevier, vol. 79(21), pages 2307-2313, November.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:21:p:2307-2313
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    Cited by:

    1. Fritjof Freise & Norbert Gaffke & Rainer Schwabe, 2021. "Convergence of least squares estimators in the adaptive Wynn algorithm for some classes of nonlinear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(6), pages 851-874, August.
    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.
    3. Arnoud V. den Boer, 2014. "Dynamic Pricing with Multiple Products and Partially Specified Demand Distribution," Mathematics of Operations Research, INFORMS, vol. 39(3), pages 863-888, August.
    4. Holger Dette & Andrey Pepelyshev & Weng Kee Wong, 2011. "Optimal Experimental Design Strategies for Detecting Hormesis," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1949-1960, December.

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