About monotone regression quantiles.

DOI10.1016/S0167-7152(99)00200-XzbMath1048.62037OpenAlexW2037443897MaRDI QIDQ1567324

Sandrine Poiraud-Casanova, Christine Thomas-Agnan

Publication date: 2000

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-7152(99)00200-x

zbMATH Keywords

MonotonicityRegression quantileMin-Max formula

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Parametric inference under constraints (62F30) Order statistics; empirical distribution functions (62G30)

Related Items (12)

Semiparametric modeling of multiple quantiles ⋮ Characterizations of Kumaraswamy Laplace distribution with applications ⋮ Bandwidth selection for kernel density estimation of fat-tailed and skewed distributions ⋮ On Quantile‐based Asymmetric Family of Distributions: Properties and Inference ⋮ Partially Linear Expectile Regression Using Local Polynomial Fitting ⋮ Multitude of Laplace distributions ⋮ Testing symmetry under a skew Laplace model. ⋮ The Two-Piece Normal-Laplace Distribution ⋮ Maximum entropy distributions with quantile information ⋮ Monotone least squares and isotonic quantiles ⋮ An R Package for Value at Risk and Expected Shortfall ⋮ Quantile Methods for Stochastic Frontier Analysis

Cites Work

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• An improved monotone conditional quantile estimator
• Monotone percentile regression
• Monotone B-Spline Smoothing
• Quantile smoothing splines
• On Estimating Monotone Parameters
• Monotone Median Regression

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