Aligned rank tests for the linear model with heteroscedastic errors

Willem Albers; Michael G. Akritas

Aligned rank tests for the linear model with heteroscedastic errors

Willem Albers, Michael G. Akritas

Research output: Book/Report › Report › Professional

Abstract

We consider the problem of testing subhypotheses in a heteroscedastic linear regression model. The proposed test statistics are based on the ranks of scaled residuals obtained under the null hypothesis. Any estimator that is n -consistent under the null hypothesis can be used to form the residuals. The error variances are estimated through a parametric model. This extends the theory of aligned rank tests to the heteroscedastic linear model. A real data set is used to illustrate the procedure.

Original language	English
Place of Publication	Enschede
Publisher	University of Twente
Number of pages	26
Publication status	Published - 1990

Publication series

Name	Memorandum
Publisher	University of Twente, Faculty of Applied Mathematics
No.	890

1 Article

Aligned rank tests for the linear model with heteroscedastic errors
Akritas, M. G. & Albers, W., 1993, In: Journal of statistical planning and inference. 37, 1, p. 23-41 19 p.
Research output: Contribution to journal › Article › Academic › peer-review

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abstract = "We consider the problem of testing subhypotheses in a heteroscedastic linear regression model. The proposed test statistics are based on the ranks of scaled residuals obtained under the null hypothesis. Any estimator that is n -consistent under the null hypothesis can be used to form the residuals. The error variances are estimated through a parametric model. This extends the theory of aligned rank tests to the heteroscedastic linear model. A real data set is used to illustrate the procedure.",

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AB - We consider the problem of testing subhypotheses in a heteroscedastic linear regression model. The proposed test statistics are based on the ranks of scaled residuals obtained under the null hypothesis. Any estimator that is n -consistent under the null hypothesis can be used to form the residuals. The error variances are estimated through a parametric model. This extends the theory of aligned rank tests to the heteroscedastic linear model. A real data set is used to illustrate the procedure.

M3 - Report

T3 - Memorandum

BT - Aligned rank tests for the linear model with heteroscedastic errors

PB - University of Twente

CY - Enschede

ER -

Aligned rank tests for the linear model with heteroscedastic errors

Abstract

Publication series

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Research output

Aligned rank tests for the linear model with heteroscedastic errors

Cite this