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 | |
| Publication status | Published - 1 Dec 2005 |
Keywords
- Jittering
- Quantile regression
- Smoothing
Fingerprint Dive into the research topics of 'Quantiles for counts'. Together they form a unique fingerprint.
Cite this
Machado, J. A. F., & Santos Silva, J. M. C. (2005). Quantiles for counts. Journal of the American Statistical Association, 100(472), 1226-1237. https://doi.org/10.1198/016214505000000330