Title

Symbolic time series analysis using hidden Markov models

Abstract

"The thesis presents two Hidden Markov Model (HMM) based methodologies for the analysis and prediction of financial time series. Both methodologies are symbolic i.e., the time series is discretized into a sequence of symbols and future symbols are predicted based on the past symbols"--Abstract, leaf iii.

Advisor(s)

Thakur, Mayur
Madria, Sanjay Kumar

Committee Member(s)

Ramakrishnan, Sreeram

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Fall 2007

Pagination

xiv, 95 leaves

Note about bibliography

Includes bibliographical references (pages 47-48).

Rights

© 2007 Nikhil Bhardwaj, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Hidden Markov models
Time-series analysis -- Mathematical models

Thesis Number

T 9303

Print OCLC #

236487038

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b6431636~S5

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