A decision theoretic approach for segmental classification using Hidden Markov models.
This paper is concerned with statistical methods for the analysis of linear sequence data using Hidden Markov Models (HMMs) where the task is to segment and classify the data according to the underlying hidden state sequence. Such analysis is commonplace in the empirical sciences including genomics,...
Main Authors: | Yau, C, Holmes, C |
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Format: | Working paper |
Language: | English |
Published: |
Oxford-Man Institute of Quantitative Finance
2009
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