ProbCast:概率预测的开源生产、评估和可视化

J. Browell, C. Gilbert
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引用次数: 7

摘要

概率预测量化了与对未来的预测相关的不确定性。当用户的目标是风险管理或非对称成本函数的优化时,它们在决策中是有用的,是必不可少的。概率预测广泛应用于金融和气象服务,并越来越多地应用于能源行业,仅举几个例子。R包ProbCast提供了一个框架,用于使用一系列领先的预测模型,以及对结果预测的可视化和评估来生成概率预测。它支持参数和非参数密度预测,以及基于高斯copula的高维依赖建模。ProbCast为与概率预测相关的常见任务提供了简单的工作流程,使领先的方法比以往任何时候都更容易获得。本文首先描述了这些特征,然后用能源预测中的一个例子进行了说明,并附带了该软件包的首次公开发布。
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ProbCast: Open-source Production, Evaluation and Visualisation of Probabilistic Forecasts
Probabilistic forecasts quantify the uncertainty associated with predictions about the future. They are useful in decision-making, and essential when the user’s objective is risk management, or optimisation with asymmetric cost functions. Probabilistic forecasts are widely utilised in finance and weather services, and increasingly by the energy industry, to name a few applications. The R package ProbCast provides a framework for producing probabilistic forecasts using a range of leading predictive models, plus visualisation, and evaluation of the resulting forecasts. It supports both parametric and non-parametric density forecasting, and high-dimensional dependency modelling based on Gaussian Copulas. ProbCast enables a simple workflow for common tasks associated with probabilistic forecasting, making leading methodologies more accessible then ever before. These features are described and then illustrated using an example from energy forecasting, and the first public release of the package itself accompanies this paper.
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