Handbook of Quantile Regression

ISBN-13: 9780367657574 / Angielski / Miękka / 2020 / 463 str.

Roger Koenker; Victor Chernozhukov; Xuming He

Opis

The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.

Spis treści

A Quantile Regression Memoir - Gilbert W. Bassett Jr. and Roger Koenker

Resampling Methods - Xuming He

Quantile Regression: Penalized - Ivan Mizera

Bayesian Quantile Regression - Huixia Judy Wang and Yunwen Yang

Computational Methods for Quantile Regression - Roger Koenker

Survival Analysis: A Quantile Perspective - Zhiliang Ying and Tony Sit

Quantile Regression for Survival Analysis - Limin Peng

Survival Analysis with Competing Risks and Semi-competing Risks Data - Ruosha Li and Limin Peng

Instrumental Variable Quantile Regression - Victor Chernozhukov, Christian Hansen, and Kaspar Wuethrich

Local Quantile Treatment Effects - Blaise Melly and Kaspar Wuethrich

Quantile Regression with Measurement Errors and Missing Data - Ying Wei

Multiple-Output Quantile Regression - Marc Hallin and Miroslav Siman

Sample Selection in Quantile Regression: A Survey - Manuel Arellano and Stephane Bonhomme

Nonparametric Quantile Regression for Banach-valued Response - Joydeep Chowdhury and Probal Chaudhuri

High-Dimensional Quantile Regression - Alexandre Belloni, Victor Chernozhukov, and Kengo Kato

Nonconvex Penalized Quantile Regression: A Review of Methods, Theory and Algorithms - Lan Wang

QAR and Quantile Time Series Analysis - Zhijie Xiao

Extremal Quantile Regression -Victor Chernozhukov, Ivan Fernandez-Val, and Tetsuya Kaji

Quantile regression methods for longitudinal data - Antonio F. Galvao and Kengo Kato

Quantile Regression Applications in Finance - Oliver Linton and Zhijie Xiao

Quantile regression for Genetic and Genomic Applications - Laurent Briollais and Gilles Durrieu

Quantile regression applications in ecology and the environmental sciences - Brian S. Cade

O autorze

Roger Koenker, University of Illinois

Victor Chernozhukov, MIT

Xuming He, University of Michigan

Limin Peng, Emory University