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Estimation of quantile density function based on regression quantiles

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  • Dodge, Yadolah
  • Jurecková, Jana

Abstract

We 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.

Suggested Citation

  • Dodge, Yadolah & Jurecková, Jana, 1995. "Estimation of quantile density function based on regression quantiles," Statistics & Probability Letters, Elsevier, vol. 23(1), pages 73-78, April.
    • Handle: RePEc:eee:stapro:v:23:y:1995:i:1:p:73-78
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    References listed on IDEAS

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    1. Falk, Michael, 1986. "On the estimation of the quantile density function," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 69-73, March.
    2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. Dodge, Yadolah & Antoch, Jaromir & Jureckova, Jana, 1991. "Computational aspects of adaptive combination of least squares and least absolute deviations estimators," Computational Statistics & Data Analysis, Elsevier, vol. 12(1), pages 87-99, August.
    4. Dodge, Yadolah & Jureckova, Jana, 1991. "Flexible L-estimation in the linear model," Computational Statistics & Data Analysis, Elsevier, vol. 12(2), pages 211-220, September.
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