Estimation of quantile density function based on regression quantiles
AbstractWe propose two estimators of quantile density function in linear regression model. The estimators, either of histogram or of kernel types, are based on regression quantiles and extend the Falk (1986) estimators based on order statistics from the location to the linear regression model. Unlike various other estimators proposed in the literature, our estimators are regression invariant and scale equivariant and hence applicable in estimation, testing, bounded-length confidence interval estimation and other inference based on L1-norm.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 23 (1995)
Issue (Month): 1 (April)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Dodge, Yadolah & Jureckova, Jana, 1991. "Flexible L-estimation in the linear model," Computational Statistics & Data Analysis, Elsevier, vol. 12(2), pages 211-220, September.
- Falk, Michael, 1986. "On the estimation of the quantile density function," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 69-73, March.
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