On the u-th Geometric Conditional Quantile

CQN (Conditional Quantile Normalization)

Conditional Expectation as Quantile Derivative

For a linear combination ∑ uj Xj of random variables, we are interested in the partial derivatives of its α-quantile Qα(u) regarded as a function of the weight vector u = (uj). It turns out that under suitable conditions on the joint distribution of (Xj) the derivatives exist and coincide with the conditional expectations of the Xi given that ∑ uj Xj takes the value Qα(u). Moreover, using this ...

Conditional Monte Carlo Estimation of Quantile Sensitivities

E quantile sensitivities is important in many optimization applications, from hedging in financial engineering to service-level constraints in inventory control to more general chance constraints in stochastic programming. Recently, Hong (Hong, L. J. 2009. Estimating quantile sensitivities. Oper. Res. 57 118–130) derived a batched infinitesimal perturbation analysis estimator for quantile sensi...

Inference on Conditional Quantile Residual Life for Censored Survival Data

Conditional Quantile Processes Based on Series or Many Regressors

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 case, for performing inference on the entire conditional quantile function and its linear functionals. ...