New Approaches to the Analysis of Count Time Series

本提案的重点是分析列举一段时间内发生的事件的数据。这种计数数据在经济学和商业中比比皆是，例如对保险索赔、贷款违约和个别产品需求的观察。该项目开发了一套用于建模和预测事件计数的创新方法。 这些方法明确地适应了数据的离散性及其随时间演变的可能复杂性。在这样做的时候，它们能够准确地推断出数据的动态结构，并准确地预测未来的事件计数。

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.