Quantiles for counts

José A. F. Machado; J. M.C. Santos Silva

doi:10.1198/016214505000000330

Quantiles for counts

José A. F. Machado, J. M.C. Santos Silva

NOVA School of Business and Economics (NOVA SBE)

Research output: Contribution to journal › Article › peer-review

238 Citations (Scopus)

Abstract

This article studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness must be artificially imposed on the problem. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimators are illustrated by simulations and an application.

Original language	English
Pages (from-to)	1226-1237
Number of pages	12
Journal	Journal of the American Statistical Association
Volume	100
Issue number	472
DOIs	https://doi.org/10.1198/016214505000000330
Publication status	Published - 1 Dec 2005

Keywords

Jittering
Quantile regression
Smoothing

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10.1198/016214505000000330

Cite this

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abstract = "This article studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness must be artificially imposed on the problem. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimators are illustrated by simulations and an application.",

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AB - This article studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness must be artificially imposed on the problem. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimators are illustrated by simulations and an application.

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KW - Smoothing

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Quantiles for counts

Abstract

Keywords

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