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 ...

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 ...

Quantile regression coefficient functions describe how the coefficients of a quantile regression model depend on the order of the quantile. A method for parametric modeling of quantile regression ...

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 ...

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 ...