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The sequential estimation in stochastic regression model with random coefficients

✍ Scribed by Sangyeol Lee

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
149 KB
Volume
61
Category
Article
ISSN
0167-7152

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✦ Synopsis

This paper considers the problem of sequential point estimation and ΓΏxed accuracy conΓΏdence set procedures of parameters in a stochastic regression model with random coe cients. The sequential estimator proposed is based on the least-squares estimator and is shown to be risk e cient as the cost of estimation error tends to inΓΏnity. Furthermore, the proposed procedure for ΓΏxed-width conΓΏdence set is shown to be both asymptotically consistent and asymptotically e cient as the width approaches zero.

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Random coe cient autoregressive processes with beta marginals provide a useful family of models for data that are both bounded and dependent over time. We obtain results on sample-size e cient sequential estimation of the mean for such processes.