As a result, running linear and quantile regression yields similar results. (Note: the QR model uses the median quantile in this example.) ...

But in neural network quantile regression, you must also watch the current quantile value to make sure you approach the desired quantile percentile value. Evaluating and Using the Neural Network ...

You can then modify the model's prediction method by adding some constant to the normal predicted values so that 80% of the predictions are greater than the associated target values. This naive ...

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 ...

We propose a penalized quantile regression and an independence screening procedure to identify important covariates and to exclude unimportant ones for a general class of ultrahigh dimensional single ...

First, we provide details of the quantile regression model for right-censored data, the inference, and the goodness of fit. Next, we illustrate the methodology with a reconstructed dataset from a ...

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 ...