Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...
Quantile regression has emerged as a significant extension of traditional linear models and its potential in survival applications has recently been recognized. In this paper we study quantile ...
Estimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile ...
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 ...
The review paper featured on the cover of the 8th issue of Advances in Atmospheric Sciences in 2024 aims to assist readers in the field of atmospheric sciences in gaining a thorough understanding of ...
BEIJING, March 9 (Xinhua) -- A global team of researchers has made strides in refining weather forecasting methods using machine learning. Scientists have been looking for better ways to make weather ...
Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation European power markets are in the midst of unprecedented changes, with a record-breaking surge in energy prices.This paper ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback