This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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379
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Type:
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Invited
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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General Methodology
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Abstract - #305977 |
Title:
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Reduced-Rank Factor Models for Network and Relational Array Data
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Author(s):
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Peter Hoff*+
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Companies:
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University of Washington
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Address:
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Box 354322, Seattle, WA, 98195-4322,
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Keywords:
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multiplicative model ;
PARAFAC ;
regularization ;
factor analysis ;
Bayes ;
MCMC
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Abstract:
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Networks and other types of relational data are often represented as matrices or arrays. For example, social network data recorded at a set of discrete time points can be represented as a three dimensional array with sender, receiver and time dimensions. Often, the main patterns in such data can be represented in terms of a low-dimensional (reduced-rank) matrix or array. In this talk we present statistical estimation methods which allow for the incorporation of reduced rank arrays into more complex models for relational data, including binary network data or longitudinal relational data.
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