Semiparametric Inference for Integer-Valued Time Series

整数值时间序列的半参数推理

• 批准号: RGPIN-2015-03889
• 负责人: Ghahramani, Melody
• 金额: $ 0.8万
• 依托单位: University of Winnipeg
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=589447
• 关键词: Semiparametric; Inference; Integer; Valued; Time

Discrete time series appear in a wide variety of settings. Energy forecasters may wish to understand patterns in the average number of windy days per month over time as a means to predicting wind power. Hydrologists may wish to forecast future river crests based on estimates of average number of rainy days. Public health officials may want to assess whether there is a declining trend in the number of cases of influenza over time after a major medical intervention such as mass immunizations.

离散时间序列出现在各种各样的设置中。能源预报员可能希望了解每月平均刮风天数随时间的变化规律，以此作为预测风力发电能力的一种手段。水文学家可能希望根据对平均雨天数的估计来预测未来的河峰。公共卫生官员可能想要评估，在大规模免疫接种等重大医疗干预之后，流感病例数量是否随着时间的推移有下降的趋势。