The Annals of Mathematical Statistics

Nonparametric Estimate of Regression Coefficients

Jana Jureckova

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Abstract

The present investigation is a follow up of [7] to a class of multiple regression problems, and is devoted to the construction of an estimate of regression parameter vector based on suitable rank statistics. Asymptotic linearity of these rank statistics in the multiple regression set up is established and the asymptotic multi-normality of the derived estimates is deduced. There exists the choice of the score-generating function to every basic distribution so that the asymptotic distribution of the estimates is the same as that of maximal-likelihood estimates.

Article information

Source
Ann. Math. Statist. Volume 42, Number 4 (1971), 1328-1338.

Dates
First available in Project Euclid: 27 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoms/1177693245

Digital Object Identifier
doi:10.1214/aoms/1177693245

Mathematical Reviews number (MathSciNet)
MR295487

Zentralblatt MATH identifier
0225.62052

JSTOR
links.jstor.org

Citation

Jureckova, Jana. Nonparametric Estimate of Regression Coefficients. Ann. Math. Statist. 42 (1971), no. 4, 1328--1338. doi:10.1214/aoms/1177693245. https://projecteuclid.org/euclid.aoms/1177693245


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