longitudinal data

Monday, September 16, 2019 - 10:30am - 11:30am
Dennis Cook (University of Minnesota, Twin Cities)
Essentially a form of targeted dimension reduction, an envelope is a construct for increasing efficiency of multivariate methods without altering traditional goals, sometimes producing gains equivalent to increasing the sample size many times over. Recognizing that the data may contain unanticipated variation that is effectively immaterial to estimation, an envelope is a subspace that envelops the material variation and thereby reduces estimative and predictive error.
Wednesday, February 21, 2018 - 8:30am - 9:10am
Mark Fiecas (University of Minnesota, Twin Cities)
In this talk, we will give an overview of statistical methodologies for spectral analysis of time series data. We will briefly discuss the common approaches for spectral analysis, and discuss their limitations for analyzing data whenever the study has a longitudinal experimental design. To address the limitations, we propose a Bayesian model for spectral analysis that accounts for the covariation within a subject.
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