Correlation analysis of survey data with the use of hidden Markov models
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Abstract
The paper proposes a new measure of the similarity between time series, based on hidden Markov models and Viterbi paths. The results are compared with the Pearson correlation coefficient. The comparison shows that the proposed measure gives more accurate estimates of the similarity and has some advantages over other measures commonly used, namely, it identifies periods (subsamples) of high and low similarity between time series.(original abstract)
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References
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