Journal of Hydrometeorology, Vol. 17, No. 6 (June 2016), pp. 1869-1883 (15 pages) ABSTRACT Classical regression models are widely used in hydrological regional frequency analysis (RFA) in order to ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

We study censored quantile regression with covariates measured with errors. We propose a composite quantile objective function based on inverse censoring-probability weighting, and an averaging ...

Immunotherapy has been approved to treat many tumor types. However, one characteristic of this therapeutic class is that survival benefit is due to late immune response, which leads to a delayed ...

The goal of a machine learning regression problem is to predict a single numeric value. Quantile regression is a variation where you are concerned with under-prediction or over-prediction. I'll phrase ...