New Approaches to the Analysis of Count Time Series

该建议的重点是对随时间推移列举事件的数据进行分析。此类统计数据在经济和商业领域比比皆是，比如对保险索赔、贷款违约和个人产品需求的观察。该项目开发了一套创新的方法来建模和预测事件计数。这些方法明确地适应了数据的离散性和随时间演变的可能的复杂性。这样，它们既可以对数据的动态结构作出准确的推断，又可以对未来的事件计数作出准确的预测。

The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evolution over time. In so doing, they enable both accurate inferences regarding the dynamic structure of the data to be drawn and accurate forecasts of future event counts to be produced.