Whittle Estimation for Lagrangian Trajectories - Regional Analysis and Environmental Consequences

拉格朗日轨迹的 Whittle 估计 - 区域分析和环境后果

• 批准号: EP/L025744/1
• 负责人: Sofia Olhede
• 金额: $ 5.56万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FL025744%2F1
• 关键词: Whittle; Estimation; Lagrangian; Trajectories; Regional

This proposal will develop new methodology for summarising the spatial information obtained from analysing multiple time series of spatial trajectories. The project will involve adapting recent methodology by the applicants for the analysis of single time series trajectories, to develop the coherent analysis of multiple trajectories observed in a given spatial region. From these advances, summaries of regional spatial structure will be proposed, as well as methods for assessing the uncertainty inherent to such summaries. In particular, as a testbed, such will be implemented for regional sets of oceanographic observations from the Global Drifter Program, which contributes to providing deeper understanding of ocean circulation and its impact on climate change. The main scope of this proposal is therefore to test the feasibility of aggregate statistical analysis of the spatial information contained in multiple sets of trajectory observations. It is an ambitious research project which, if successful, would open the door to a wide set of applications such as ecology, oceanography and traffic management.

该提案将开发新的方法，用于总结从分析空间轨迹的多个时间序列中获得的空间信息。该项目将涉及调整申请人最近用于分析单一时间序列轨迹的方法，以便对在给定空间区域观察到的多个轨迹进行连贯分析。根据这些进展，将提出区域空间结构的摘要，以及评估此类摘要固有的不确定性的方法。特别是，作为一个试验平台，将为全球漂流者方案的区域海洋学观测集实施这一系统，这有助于更深入地了解海洋环流及其对气候变化的影响。因此，本建议的主要范围是测试对多组轨迹观测所含空间信息进行综合统计分析的可行性。这是一个雄心勃勃的研究项目，如果成功，将为生态学，海洋学和交通管理等广泛的应用打开大门。

项目成果

The debiased Whittle likelihood

• DOI: 10.1093/biomet/asy071
• 发表时间: 2019-02
• 期刊: Biometrika
• 影响因子: 2.7
• 作者: A. Sykulski;S. Olhede;Arthur Guillaumin;J. Lilly;J. Early

A Widely Linear Complex Autoregressive Process of Order One

• DOI: 10.1109/tsp.2016.2599503
• 发表时间: 2015-11
• 期刊: IEEE Transactions on Signal Processing
• 影响因子: 5.4
• 作者: A. Sykulski;S. Olhede;J. Lilly

Frequency-Domain Stochastic Modeling of Stationary Bivariate or Complex-Valued Signals

平稳二变量或复值信号的频域随机建模

• DOI: 10.1109/tsp.2017.2686334
• 发表时间: 2017
• 期刊: IEEE Transactions on Signal Processing
• 影响因子: 5.4
• 作者: Sykulski A

A Power Variance Test for Nonstationarity in Complex-Valued Signals

复值信号非平稳性的幂方差检验

• DOI: 10.1109/icmla.2015.122
• 发表时间: 2015
• 作者: Bartlett T

ANALYSIS OF NON-STATIONARY MODULATED TIME SERIES WITH APPLICATIONS TO OCEANOGRAPHIC SURFACE FLOW MEASUREMENTS

• DOI: 10.1111/jtsa.12244
• 发表时间: 2017-09-01
• 期刊: JOURNAL OF TIME SERIES ANALYSIS
• 影响因子: 0.9
• 作者: Guillaumin, Arthur P.;Sykulski, Adam M.;Lilly, Jonathan M.
• 通讯作者: Lilly, Jonathan M.