Monday, September 16, 2019 - 1:30pm - 2:30pm
Ian McKeague (Columbia University)
This talk introduces a nonparametric framework for analyzing physiological sensor data collected from wearable devices. The idea is to apply the stochastic process notion of occupation times to construct activity profiles that can be treated as monotonically decreasing functional data. Whereas raw sensor data typically need to be pre-aligned before standard functional data methods are applicable, activity profiles are automatically aligned because they are indexed by activity level rather than by follow-up time.
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