Mathematical Sciences: Model Selection for Mixtures

数学科学：混合物的模型选择

• 批准号: 9505196
• 负责人: Dominique Haughton
• 金额: $ 3万
• 依托单位: Bentley University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-01 至 1997-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9505196&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Model; Selection; Mixtures

Proposal: DMS 9505196 PI: Dominique Haughton Institution: Bentley College Title: Model Selection for Mixtures Abstract This research is concerned with the problem of selecting a suitable model when the competing models involve mixtures of distributions. Criteria for model selection among mixtures and convolutions of exponential distributions are proposed and shown to be asymptotically close to Bayes procedures. The performance of the criteria are compared to that of complexity based model selection criteria. The methodology is then applied to data from ethological science. The case of mixtures of multiple regression models and logistic regression models is also considered and applied to the problem of testing for son preference in Vietnam, using data from the Vietnam Living Standard Survey. In many modeling situations, a single model is not suitable for all the data. For example, when investigating whether there is significant statistical evidence of son preference (preference for boys over girls) in countries such as Vietnam, the problem is complicated by the fact that some families display son preference and some do not. In ethological science, an area of behavioral science concerned with detailed observation and recording of the behavior of one or more individuals, interesting questions arise as to whether a behavior can be split into consecutive activities or is a mixture of several activities. These problems can be addressed by modeling with statistical mixtures.

提案：DMS 9505196 PI：Dominique豪顿机构：Bentley College标题：混合物模型选择 摘要 本研究探讨当竞争模型包含混合分布时，如何选择合适的模型。 指数分布的混合物和卷积之间的模型选择的标准提出，并示出渐近接近贝叶斯程序。 的标准的性能进行比较，基于复杂性的模型选择标准。 然后将该方法应用于动物行为学科学的数据。 多元回归模型和逻辑回归模型的混合物的情况下，也被认为是适用于在越南的儿子偏好测试的问题，使用越南生活水平调查的数据。 在许多建模情况下，单个模型并不适合所有数据。 例如，在调查越南等国是否存在重男轻女的重要统计证据时，问题是 有些家庭表现出对儿子的偏爱，有些则没有。 在动物行为学中，行为科学的一个领域 一门关于详细观察和记录一个或多个个体行为的科学，有趣的问题出现了，一个行为是否可以分为连续的活动或几个活动的混合。 这些问题可以 通过使用统计混合物建模来解决。