Exposure data with repeated measures from occupational studies are frequently right-skewed and left-censored. To address right-skewed data, data are generally log-transformed and analyses modeling the ...

Quantile regression robustly estimates the typical and extreme values of a response. QR explores the effect of one or more predictors on quantiles of the response. Unlike in traditional mean ...

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 ...

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 ...

In this paper we propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter ...

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...

This paper examines a set of value-at-risk (VaR) models and their ability to appropriately describe and capture price-change risk in the European energy market. We make in-sample, one-day-ahead VaR ...