This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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189
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Type:
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Invited
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Date/Time:
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Monday, August 2, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #308622 |
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Title:
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Generic Framework for Parallel Statistical Computing
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Author(s):
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Hana Sevcikova*+
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Companies:
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University of Washington
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Address:
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, Seattle, WA, ,
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Keywords:
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parallel computing ;
statistical simulations ;
fault-tolerance ;
reproducibility ;
R package ;
snowFT
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Abstract:
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The time-consuming methods popular in modern statistics require efficient use of available computing resources. The potential benefits of parallel computing are well known but among statisticians are not widely realized in practice. I will present a generic framework for parallel statistical simulations, called snowFT, that overcomes several obstacles in parallel programming. It generates reproducible results, it is fault tolerant, it ensures load balancing and computation transparency. It is implemented as an R package and its ease of use makes parallel processing accessible even to non-programmers. I will demonstrate snowFT on several examples.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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