Abstract Details
Activity Number:
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482
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #308558 |
Title:
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Time Series Data with Semi-Reflective Boundaries: Single-Pass and Iterative Methods
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Author(s):
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Jeffrey D. Dawson*+ and Amy M. Johnson
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Companies:
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The University of Iowa and Univ of Iowa
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Keywords:
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Spatial/temporal model ;
Grid search ;
Driving studies ;
Likelihood
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Abstract:
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Some time series data have values that tend to reflect back towards the middle of their range. For example, a motor vehicle that that starts to cross its lane boundaries may be promptly directed back toward the middle of the desired driving lane. Dawson et al (2010) proposed a model to accommodate such boundaries, using third-order polynomial projections plus an error term whose sign and magnitude are modeled stochastically. They fit this model using a single pass approach involving a combination of linear and logistic regression. In this report, we explore iterative likelihood-based methods to fit this model, as well as a new single pass method. We do these comparisons using simulated data, as well as vehicular control data from 127 middle-aged and elderly drivers. This work was supported by NIH/NIA awards AG17177 and AG15071.
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Authors who are presenting talks have a * after their name.
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