Lan Luo - Colloquium Speaker

Assistant Professor, Department of Statistics and Actuarial Science, University of Iowa
Thursday, September 17, 2020 - 3:15pm
Colloquium Title: 
Renewable Estimation and Incremental Inference with Streaming Datasets


New data collection and storage technologies have given rise to a new field of streaming data analytics, including real-time statistical methodology for online data analyses. Streaming data refers to high-throughput recordings with large volumes of observations gathered sequentially and perpetually over time. Such data collection scheme is pervasive not only in biomedical sciences such as mobile health, but also in other fields such as IT, finance, service and operations, etc. Despite a large amount of work in the field of online learning, very few focus on statistical inference and most of them are based on homogeneity assumption. In the first half of this talk, I will introduce a real-time regression analysis method, termed as “renewable estimation”, in the context of cross-sectional data streams, with a particular objective of addressing challenges in streaming data storage and computational efficiency. In the second half, I will discuss an extension to data streams that involve both inter-data batch correlation and dynamic heterogeneity. The key technical novelty pertains to the fact that the proposed method uses current data and summary statistics of historical data. The proposed algorithm will be demonstrated in generalized linear models (GLM) for cross-sectional data and state space mixed models (SSMM) for correlated data. I will provide both conceptual understanding and theoretical guarantees of the proposed method, and illustrate its performance via numerical examples. I will also briefly discuss several future directions at the end of this talk.


Everyone is welcome to join! Please note that the meeting opens at 3:15pm, and the presentation is at 3:30-4:20pm. There will be time afterward for Q&A with the speaker.

Topic: Colloquia: Department of Statistics and Actuarial Science, The University of Iowa

Time: Sep 17, 2020 03:15 PM Central Time (US and Canada)

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Meeting ID: 970 2130 9544