Development of Conditionally Specified Statistical Models for Analysis of Environmental Studies

- 建议书编号：DMS 981663 主要研究者： Mark S Kaiser，Michael J. Daniels，Soumendra Lahiri Institution： 爱荷华州州立大学项目： 发展中国家专项统计 环境研究分析模型 摘要： 这个计画的目标是制定具有不同形式的条件分布的弹性多元分布，从这些分布发展统计模型，并评估 这些模型在描述和预测环境变量的能力方面的表现。 这类模型特别适合于处理涉及空间依赖性过程的问题，如陆地环境中空气污染物和潜在有毒物质的浓度。 这些统计方法将提高我们在监测地点描述这些变量的能力，特别是对未监测地点进行准确和精确的预测。 由此得出的污染物的空间和时间平均值将更好地评估环境暴露 用于人类健康影响和环境条件的生态反应模型。

----------------------------------------------------------------------- Proposal Number: DMS 9816630 PI: Mark S Kaiser, Michael J. Daniels, Soumendra Lahiri Institution: Iowa State University Project: Development of Conditionally Specified Statistical Models for Analysis of Environmental Studies Abstract: The objectives of this project are to formulate flexible multivariate distributions having associated conditional distributions of varying forms, develop statistical models from these distributions, and assess the performance of such models in terms of their ability to describe and predict environmental variables. Such models are particularly attractive for application to problems that involve spatially dependent processes, such as concentrations of air pollutants and potentially toxic substances in terrestrial settings. These statistical methods will improve our ability to describe such variables at monitored locations and, in particular, produce accurate and precise predictions for unmonitored locations. Spatial and temporal averages of pollutants that result will provide better assessment of environmental exposures for use in models of human health impacts and ecological responses to environmental conditions.