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Dual Regression

Richard Spady, Sami Stouli

arXiv 25 Oct 2012 · Statistics — Methodology · publishedBiometrika (2017) · 7 citations (OpenAlex)

arXiv:1210.6958 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution functions which, in its simplest form, is the dual program of a simultaneous estimator for linear location-scale models. We apply our general characterization to the specification and estimation of a flexible class of conditional distribution functions, and present asymptotic theory for the corresponding empirical dual regression process.

Citation extraction

24
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Boyd, S. P. and Vandenberghe, L (2004) Convex Optimization0.5854325%
2Chernozhukov, V., Fernandez-Val, I. & Galichon, A (2010) Quantile and probability curves without crossing0.5112250%
3He, X (1997) Quantile Curves without Crossing0.5112250%
4Koenker, R. & Xiao, Z (2002) Inference on the quantile regression process0.5112250%
5Koenker, R (2005) Quantile Regression. Cambridge University Press0.51121100%
6Bondell, H., Reich, B. and Wang, H (2010) Noncrossing quantile regression curve estimation0.4816217%
7Carlier, G., Chernozhukov, V., & Galichon, A (2016) Vector quantile regression: an optimal transport approach0.40511100%
8Chernozhukov, V., Fernandez-Val, I. & Melly, B (2013) Inference on Counterfactual Distributions0.40511100%
9Cosma, A., Scaillet, O., & Von Sachs, R (2007) Multivariate wavelet-based shape-preserving estimation for dependent observations0.40511100%
10De Vore, R (1977) Monotone approximation by splines0.40511100%

Showing the top 10 of 24 scored citations.