Rank-based analysis of the heteroscedastic linear model.

From: Journal of the American Statistical Association | Date: June 1, 1996| Author: | Copyright information

The use of rank-based estimates for scale and regression coefficients in the analysis of the heteroscedastic problem is proposed. The class of R estimates is used to initially estimate beta, where beta is the vector if regression coefficients. The approach easily obtains the asymptotic distributions of scale and regression coefficient estimators, along with consistent standard error estimates.

1. INTRODUCTION

Heteroscedasticity occurs frequently in linear models. For example, this has been a major problem in many of the dose-response-type data sets drawn from pharmaceutical science ...

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