Quantile Regression (Econometric Society Monographs)

Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. Roger Koenker has devoted more than 25 years of research to the topic. The methods in his analysis are illustrated with a variety of applications from economics, biology, ecology and finance and will target audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above. Author resource page: http://www.econ.uiuc.edu/~roger/research/rq/rq.html

Roger Koenker is the winner of the 2010 Emanuel and Carol Parzen Prize for Statistical Innovation, awarded by the the Department of Statistics at Texas A&M University.

• Quantile Regression (Quantitative Applications in the Social Sciences) (v. 149)
• Handbook of Quantile Regression (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
• Quantile Regression: Estimation and Simulation (Wiley Series in Probability and Statistics)
• Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)
• Quantile Regression: Theory and Applications
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
• Deep Learning (Adaptive Computation and Machine Learning series)
• Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data