Abstract:

A major challenge in the age of Big Data is the integration of disparate data types into a data analysis. That is tackled here in the context of data blocks measured on a common set of experimental cases. This data structure motivates the simultaneous exploration of the joint and individual variation within each data block. DIVAS improves earlier methods using a novel random direction approach to statistical inference, and by treating partially shared blocks. Usefulness is illustrated using mortality, cancer and neuroimaging data sets.

ZOOM INVITATION

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: Mar 11, 2020 03:15 PM Central Time (US and Canada)

Join Zoom Meeting

https://uiowa.zoom.us/j/94952892803

Meeting ID: 949 5289 2803

One tap mobile

+13126266799,,94952892803# US (Chicago)

+16468769923,,94952892803# US (New York)

Dial by your location

        +1 312 626 6799 US (Chicago)

        +1 646 876 9923 US (New York)

        +1 301 715 8592 US (Washington DC)

        +1 346 248 7799 US (Houston)

        +1 669 900 6833 US (San Jose)

        +1 253 215 8782 US (Tacoma)

Meeting ID: 949 5289 2803

Find your local number: https://uiowa.zoom.us/u/ac38DWF69h

Join by SIP

94952892803@zoomcrc.com

Join by H.323

162.255.37.11 (US West)

162.255.36.11 (US East)

115.114.131.7 (India Mumbai)

115.114.115.7 (India Hyderabad)

213.19.144.110 (Amsterdam Netherlands)

213.244.140.110 (Germany)

103.122.166.55 (Australia Sydney)

103.122.167.55 (Australia Melbourne)

64.211.144.160 (Brazil)

69.174.57.160 (Canada Toronto)

65.39.152.160 (Canada Vancouver)

207.226.132.110 (Japan Tokyo)

149.137.24.110 (Japan Osaka)

Meeting ID: 949 5289 2803