Aspects of inference for the Influence Model and related graphical models
Name
57418331-MIT.pdf
Description
Full printable version
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4.01 MB
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Checksum (MD5)
4d72ae085975ecc79902c65a9edae9f4
Author(s)
Jammalamadaka, Arvind K. (Arvind Kumar), 1981-
Advisor(s)
George C. Verghese.
Alternative Title
Aspects of inference for the IM and related graphical models
Date Issued
2004
Publisher
Massachusetts Institute of Technology
Abstract
The Influence Model (IM), developed with the primary motivation of describing network dynamics in power systems, has proved to be very useful in a variety of contexts. It consists of a directed graph of interacting sites whose Markov state transition probabilities depend on their present state and that of their neighbors. The major goals of this thesis are (1) to place the Influence Model in the broader framework of graphical models, such as Bayesian networks, (2) to provide and discuss a hybrid model between the IM and dynamic Bayesian networks, (3) to discuss the use of inference tools available for such graphical models in the context of the IM, and (4) to provide some methods of estimating the unknown parameters that describe the IM. We hope each of these developments will enhance the use of IM as a tool for studying networked interact ions.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 61-64).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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