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

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.
Liste complète des métadonnées

Cited literature [13 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00416008
Contributor : Luc Pronzato <>
Submitted on : Friday, September 11, 2009 - 4:07:39 PM
Last modification on : Monday, November 5, 2018 - 3:52:02 PM
Document(s) archivé(s) le : Tuesday, June 15, 2010 - 11:34:07 PM

File

SPL-2009-REV.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Luc Pronzato. Asymptotic properties of nonlinear estimates in stochastic models with finite design space. Statistics and Probability Letters, Elsevier, 2009, 79, pp.2307-2313. ⟨10.1016/j.spl.2009.07.025⟩. ⟨hal-00416008⟩

Share

Metrics

Record views

237

Files downloads

120