399 citations · 407 across the 9 of their papers we have counts for
4 papers · 1 filter
Extremal Quantile Regression: An Overview
Victor Chernozhukov, Iván Fernández-Val, Tetsuya Kaji
Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts with an increasing number of economic and financial applications…
quantreg.nonpar: An R Package for Performing Nonparametric Series Quantile Regression
Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov +1
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point…
Counterfactual: An R Package for Counterfactual Analysis
Mingli Chen, Victor Chernozhukov, Iván Fernández-Val +1
The Counterfactual package implements the estimation and inference methods of Chernozhukov, Fernández-Val and Melly (2013) for counterfactual analysis. The counterfactual distribut…
Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes
Victor Chernozhukov, Iván Fernández-Val, Blaise Melly +1
Quantile and quantile effect functions are important tools for descriptive and causal analyses due to their natural and intuitive interpretation. Existing inference methods for the…