The Annals of Mathematical Statistics

On a Class of Rank Order Tests for Regression with Partially Informed Stochastic Predictors

Malay Ghosh and Pranab Kumar Sen

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Abstract

Hajek (1962) has obtained asymptotically most powerful rank order tests for simple linear regression with non-stochastic predictors. His findings are extended here to the multiple linear regression model with stochastic predictors, including the situations where the predictors are partially informed. The proposed tests are shown to be conditionally distribution-free. Their asymptotic properties and efficiencies are studied, and the asymptotic optimality is established under the conditions of Wald (1943).

Article information

Source
Ann. Math. Statist., Volume 42, Number 2 (1971), 650-661.

Dates
First available in Project Euclid: 27 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoms/1177693415

Digital Object Identifier
doi:10.1214/aoms/1177693415

Mathematical Reviews number (MathSciNet)
MR305516

Zentralblatt MATH identifier
0215.54403

JSTOR
links.jstor.org

Citation

Ghosh, Malay; Sen, Pranab Kumar. On a Class of Rank Order Tests for Regression with Partially Informed Stochastic Predictors. Ann. Math. Statist. 42 (1971), no. 2, 650--661. doi:10.1214/aoms/1177693415. https://projecteuclid.org/euclid.aoms/1177693415


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