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An Empirical Quantile Function for Linear Models with |operatornameiid Errors
Gilbert Bassett, Jr. and Roger Koenker
Journal of the American Statistical Association
Vol. 77, No. 378 (Jun., 1982), pp. 407-415
Stable URL: http://www.jstor.org/stable/2287261
Page Count: 9
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The regression quantile statistics of Koenker and Bassett (1978) are employed to construct an estimate of the error quantile function in linear models with iid errors. Some finite sample properties and the asymptotic behavior of the proposed estimator are derived. Comparisons with procedures based on residuals are made. The stackloss data of Brownlee (1965) is reanalyzed to illustrate the technique.
Journal of the American Statistical Association © 1982 American Statistical Association