Abstract Details
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Activity Number:
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322
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract #312302
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Title:
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Uncertainty Quantification for Massive Data Problems Using Generalized Fiducial Inference
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Author(s):
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Thomas C.M. Lee*+ and Jan Hannig and Randy C.S. Lai
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Companies:
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University of California, Davis and University of North Carolina at Chapel Hill and University of California, Davis
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Keywords:
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parallel processing ;
big data
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Abstract:
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In this talk we present a novel method for computing parameter estimates and their standard errors for massive data problems. The method is based on generalized fiducial inference.
This is joint work with Jan Hannig and Randy Lai.
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Authors who are presenting talks have a * after their name.
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