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Conditional quantile processes based on series or many regressors

Belloni, Alexandre; Chernozhukov, Victor; … - 2011

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework, covering many regressors as a special...

Persistent link: https://www.econbiz.de/10009153247

Risk margin quantile function via parametric and non-parametric Bayesian approaches

Dong, Alice X. D.; Chan, Jennifer S. K.; Peters, Gareth W. - In: Astin bulletin : the journal of the International … 45 (2015) 3, pp. 503-550

Persistent link: https://www.econbiz.de/10011397246

Nonparametric quantile frontier estimation under shape restriction

Wang, Yongqiao; Wang, Shouyang; Dang, Chuangyin; Ge, Wenxiu - In: European journal of operational research : EJOR 232 (2014) 3, pp. 671-678

Persistent link: https://www.econbiz.de/10010224949

Conditional quantile processes based on series or many regressors

Belloni, Alexandre; Chernozhukov, Victor; Chetverikov, Denis - 2016 - This version of August 28, 2016

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR-series framework, covering many regressors as a special...

Persistent link: https://www.econbiz.de/10011525883