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The sequential estimation in stochastic regression model with random coefficients

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  • Lee, Sangyeol

Abstract

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

Suggested Citation

  • Lee, Sangyeol, 2003. "The sequential estimation in stochastic regression model with random coefficients," Statistics & Probability Letters, Elsevier, vol. 61(1), pages 71-81, January.
    • Handle: RePEc:eee:stapro:v:61:y:2003:i:1:p:71-81
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    References listed on IDEAS

    as
    1. Lee, Sangyeol & Sriram, T. N., 1999. "Sequential point estimation of parameters in a threshold AR(1) model," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 343-355, December.
    2. Fakhrezakeri, I. & Lee, S. Y., 1993. "Sequential Estimation of the Mean Vector of a Multivariate Linear Process," Journal of Multivariate Analysis, Elsevier, vol. 47(2), pages 196-209, November.
    3. Martinsek Adam T., 1995. "Estimating A Slope Parameter In Regression With Prescribed Proportional Accuracy," Statistics & Risk Modeling, De Gruyter, vol. 13(4), pages 363-378, April.
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