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Activity Number:
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693
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #320299
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View Presentation
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Title:
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Space-Filling Exploratory Experimental Design
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Author(s):
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Kasturi Talapatra* and Eric Laber and Leonard Stefanski
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Companies:
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North Carolina State University and North Carolina State University and North Carolina State University
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Keywords:
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reproducible research ;
simulation experiments ;
reproducibility ;
optimization ;
object oriented programming ;
Monte Carlo
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Abstract:
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Monte Carlo simulations are widely used to study and compare statistical methodologies. Space-filling Exploratory Experimental Designs (SEEDs) are a general approach to designing and evaluating simulation experiments to form general and reproducible conclusions. SEED obtains performance measures of methods on a very large number of generative models that are systematically varied to ensure coverage within a space of models using optimization algorithms. Statistical modeling techniques are used to characterize how features of the underlying generative models affect performance. SEED is implemented using object oriented programming to facilitate reproducibility.
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Authors who are presenting talks have a * after their name.
