The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Quantile regression: applications and current research areas
Abstract
Summary. Quantile regression offers a more complete statistical model than mean regression and now has widespread applications. Consequently, we provide a review of this technique. We begin with an introduction to and motivation for quantile regression. We then discuss some typical application areas. Next we outline various approaches to estimation. We finish by briefly summarizing some recent research areas.
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Cites
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Self-citationMonte Carlo Methods in Bayesian Computation
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Elsner, J. B., Kossin, J. P., & Jagger, T. H. (2008) · Nature · doi:10.1038/nature07234 · Cited by 1,184
Gibbs sampling methods for Bayesian quantile regression
Kozumi, H., & Kobayashi, G. (2011) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2010.496117 · Cited by 498
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Härdle, W. K., Wang, W., & Yu, L. (2016) · Journal of Econometrics · doi:10.1016/j.jeconom.2016.02.013 · Cited by 470
COVID-19 predictability in the United States using Google Trends time series
Mavragani, A., & Gkillas, K. (2020) · Scientific Reports · doi:10.1038/s41598-020-77275-9 · Cited by 140
Castino, F., Bookhagen, B., & Strecker, M. R. (2017) · Climate Dynamics · doi:10.1007/s00382-016-3127-2 · Cited by 49
Metadata
- Authors
- Yu, K., Lu, Z., & Stander, J.
- Venue
- Journal of the Royal Statistical Society: Series D (The Statistician)
- Publisher
- Wiley
- Published
- 2003-10
- Volume
- 52
- Issue
- 3
- Pages
- 331-350
- ISSN
- 0039-0526 (ISSN-L)
- 1467-9884
- OpenAlex
- W2147646644
- Cited by
- 686
- References
- 29
- FWCI
- 9.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yu, K., Lu, Z., & Stander, J. (2003). Quantile regression: applications and current research areas. Journal of the Royal Statistical Society: Series D (The Statistician). https://doi.org/10.1111/1467-9884.00363
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
