Asymptotic normality of the lengths of a class of nonparametric confidence intervals for a regression parameter

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Date

1984-09

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Canadian Journal of Statistics

Abstract

In the linear regression model, the asymptotic distributions of certain functions of confidence bounds of a class of confidence intervals for the regression parameter arc investigated. The class of confidence intervals we consider in this paper are based on the usual linear rank statistics (signed as well as unsigned). Under suitable assumptions, if the confidence intervals are based on the signed linear rank statistics, it is established that the lengths, properly normalized, of the confidence intervals converge in law to the standard normal distributions; if the confidence intervals arc based on the unsigned linear rank statistics, it is then proved that a linear function of the confidence bounds converges in law to a normal distribution.

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Publisher's, offprint version

Keywords

Rank statistics, linear regression model, confidence intervals, asymptotic normality

Citation

Puri, M. L. "Asymptotic normality of the lengths of a class of nonparametric confidence intervals for regression parameters." Canadian Journal of Statistics (1984), Volume 12 Issue 3, 217–228. Co-author: T.J. Wu.

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