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

Authors
  • Pronzato, Luc
Publication Date
Jan 01, 2009
Identifiers
DOI: 10.1016/j.spl.2009.07.025
OAI: oai:HAL:hal-00416008v1
Source
HAL
Keywords
Language
English
License
Unknown
External links

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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