Conference: EnviBayes Workshop on Complex Environmental Data

这场名为“环境贝叶斯复杂环境数据研讨会”的研讨会将于2023年9月18日至20日在科罗拉多州的柯林斯堡举行。环境和生态数据往往是复杂和多样的。这种复杂性可能源于错综复杂的数据生成机制，例如生态学研究中存在许多相互作用的物种，或者源于结构相关性，例如空气污染测量的空间和时间相关性。因此，环境和生态数据集的分析可能需要专门的统计和计算工具来适当地捕捉和说明复杂性。虽然生态和环境统计社区不大，但很容易在各自的子社区中成为孤岛。然而，一种类型的依赖关系(和数据)的建模方法和工具的进步通常可以有益地扩展到另一种类型的依赖关系，并对多个应用领域产生重大影响。因此，与环境和生态数据的不同方面合作的统计学家彼此互动，在我们的次级社区中传播知识，以促进所有学科的进步，这将是有益的。研讨会将有以下主要目标：i)为环境和生态统计中的子社区提供一个场所，分享其自身网络中的前沿进展，以进一步激发更深层次的知识收获；ii)在子社区之间转移知识并促进合作。环境贝叶斯复杂环境数据研讨会的计划包括：i)环境健康和流行病学；ii)遥感数据；iii)空间和时间相关性模型；iv)多变量和空间极端情况；v)使用气候模型预测未来极端情况；vi)动物运动和丰度模型；vii)与复杂计算机模型有关的统计推断。该项目将鼓励研究生、职业生涯早期研究人员和统计中代表性不足群体的成员参与。有关研讨会的更多详细信息，请访问：https://statistics.colostate.edu/envibayes-workshop/.This奖项反映了国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This workshop titled "EnviBayes Workshop on Complex Environmental Data" will be held in Fort Collins, Colorado on September 18-20, 2023. Environmental and ecological data are often complex and diverse. This complexity may arise from intricate data-generating mechanisms, such as the presence of many interacting species in an ecological study, or from structural dependence, such as correlation in space and time of air pollution measurements. As such, analysis of environmental and ecological datasets may require specialized statistical and computational tools to appropriately capture and account for the complexity. While the ecological and environmental statistics community is not large, it is easy to become siloed in each of the respective sub-communities. However, the advances in modeling approaches and tools for one type of dependence (and data) can often be usefully extended to another type of dependence and have a large impact on multiple application areas. It can therefore benefit statisticians working with different facets of environmental and ecological data to interact with each other to propagate knowledge among our sub-communities for the increased advancement of all disciplines. The workshop will have the following major aims: i) to provide sub-communities within environmental and ecological statistics with a venue to share cutting-edge advancements within their own networks to further spark deeper knowledge gains; ii) to transfer knowledge between sub-communities and foster collaboration.The program of the EnviBayes Workshop on Complex Environmental Data includes: i) Environmental Health and Epidemiology; ii) Data from Remote Sensing; iii) Models for Spatial and Temporal Dependence; iv) Multivariate and Spatial Extremes; v) Using Climate Models to Project Future Extremes; vi) Models for Animal Movement and Abundance; vii) Statistical Inference Related to Complex Computer Models. This project will encourage the participation of graduate students, early-career researchers, and members of groups under-represented in statistics. More details about the workshop can be found at: https://statistics.colostate.edu/envibayes-workshop/.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.