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September, 1992 An Improved Sequential Procedure for Estimating the Regression Parameter in Regression Models with Symmetric Errors
T. N. Sriram
Ann. Statist. 20(3): 1441-1453 (September, 1992). DOI: 10.1214/aos/1176348777

Abstract

A sequential procedure for estimating the regression parameter $\beta \in R^k$ in a regression model with symmetric errors is proposed. This procedure is shown to have asymptotically smaller regret than the procedure analyzed by Martinsek when $\mathbf{\beta} = \mathbf{0}$, and the same asymptotic regret as that procedure when $\mathbf{\beta} \neq \mathbf{0}$. Consequently, even when the errors are normally distributed, it follows that the asymptotic regret can be negative when $\mathbf{\beta} = \mathbf{0}$. These results extend a recent work of Takada dealing with the estimation of the normal mean, to both regression and nonnormal cases.

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T. N. Sriram. "An Improved Sequential Procedure for Estimating the Regression Parameter in Regression Models with Symmetric Errors." Ann. Statist. 20 (3) 1441 - 1453, September, 1992. https://doi.org/10.1214/aos/1176348777

Information

Published: September, 1992
First available in Project Euclid: 12 April 2007

zbMATH: 0782.62079
MathSciNet: MR1186258
Digital Object Identifier: 10.1214/aos/1176348777

Subjects:
Primary: 62L12
Secondary: 60G40, 62J05

Rights: Copyright © 1992 Institute of Mathematical Statistics

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Vol.20 • No. 3 • September, 1992
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