重新建模：定量回归平均模型

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-09-24 DOI:10.1016/j.softx.2024.101905

Grzegorz Zakrzewski , Kacper Skonieczka , Mikołaj Małkiński , Jacek Mańdziuk

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引用次数: 0

摘要

电价预测对于在电力市场中做出明智的商业决策至关重要。概率预测提供了一系列可能的未来价格，而不是单一的估计值，对于捕捉市场的不确定性尤为重要。定量回归平均法 (QRA) 是生成这些概率预测的主要方法。在本文中，我们将介绍 ReModels，这是一个综合性 Python 软件包，用于实现 QRA 及其最近文献中的各种修改。该软件包不仅提供 QRA 工具，还包括数据采集、准备和方差稳定变换（VST）功能。据我们所知，目前还没有 QRA 及其变体的公开实现。我们的软件包旨在填补这一空白，为研究人员和从业人员提供在电价预测领域生成准确可靠的概率预测的工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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ReModels: Quantile Regression Averaging models

Electricity price forecasts are essential for making informed business decisions within the electricity markets. Probabilistic forecasts, which provide a range of possible future prices rather than a single estimate, are particularly valuable for capturing market uncertainties. The Quantile Regression Averaging (QRA) method is a leading approach to generating these probabilistic forecasts. In this paper, we introduce ReModels, a comprehensive Python package that implements QRA and its various modifications from recent literature. This package not only offers tools for QRA but also includes features for data acquisition, preparation, and variance stabilizing transformations (VSTs). To the best of our knowledge, there is no publicly available implementation of QRA and its variants. Our package aims to fill this gap, providing researchers and practitioners with the tools to generate accurate and reliable probabilistic forecasts in the field of electricity price forecasting.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.