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澳大利亚莫纳什大学Prof. Rob Hyndman特邀报告

发布时间: 2017/11/28 08:18:15     点击次数:次   打印本页

【北航经商大讲堂第16期】

澳大利亚莫纳什大学Prof. Rob Hyndman特邀报告

题目: Optimal Forecast Reconciliation

 

最优时间序列预测和解方法

 

主讲人:Prof. Rob Hyndman

 

澳大利亚莫纳什大学

 

主持人:范英 教授

时间: 2017年11月30日14:30-16:30

地点: 北航新主楼A座618

摘要:

Time series can often be naturally disaggregated in a hierarchical or grouped

structure. For example, a manufacturing company can disaggregate total demand

for their products by country of sale, retail outlet, product type, package

size, and so on. As a result, there can be millions of individual time series to

forecast at the most disaggregated level, plus additional series to forecast at

higher levels of aggregation.

A common constraint is that the disaggregated forecasts need to add up to the

forecasts of the aggregated data. This is known as forecast “coherence”. When we

turn incoherent forecasts into coherent forecasts, we call it “forecast

reconciliation”.I will show that the optimal reconciliation method involves fitting a

linear regression model where the design matrix has one column for each of the series at the most

disaggregated level. But with huge numbers of time series, the model is

impossible to estimate using standard regression algorithms. I will show how the

hts package for R solves this problem.

时间序列通常可以自然分解成层次结构或分组结构。例如,制造公司可以按销售国家,零售店,产品类型,包装大小等分解其产品的总需求。因此,在最底层可以有数百万个单独的时间序列需要进行预测,另外在更高层次还有更多的时间序列需要预测。

在此预测过程中,最大的限制就是底层的预测都需要加总到高层的预测。这被称为预测的“一致性”。当我们把不一致的预测变成一致的预测时,我们称之为“预测和解”。我将展示一个最佳的协调方法,这个方法涉及拟合一个线性回归模型,其中设计矩阵对于每个时间序列在最底层具有一列。但是,如果有大量的时间序列,则使用标准回归算法无法估计模型。我将展示如何在R的hts包中解决这个问题。

主讲人简介:

Rob Hyndman is Professor of Statistics in the Department of Econometrics and

Business Statistics at Monash University. He is also Editor-in-Chief of theInternational Journal of Forecastingand

a Director of the International Institute of Forecasters. Rob is the author of

over 150 research papers and 5 books in statistical science. In 2007, he

received the Moran medal from the Australian Academy of Science for his contributions to

statistical research, especially in the area of statistical forecasting. For

over 30 years, Rob has maintained an active consulting practice, assisting

hundreds of companies and organizations around the world. He has won awards for

his research, teaching, consulting and graduate supervision.

Rob Hyndman教授是澳大利亚莫纳什大学计量经济学和商业统计系教授。他还担任“International Journal of Forecasting”杂志的主编和国际预测者协会的主任。Rob是超过150篇研究论文和5本统计科学相关著作的作者。2007年,因其对统计研究的贡献尤其是在统计预测领域的贡献,他获得了澳大利亚科学院的Moral Medal。30多年来,Rob做了大量的咨询工作,协助全球数百家公司和组织进行预测研究。他在研究、教学、咨询和学生指导方面获得了众多奖项。