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Volumn 39, Issue 4, 2011, Pages 1-22

Hidden semi markov models for multiple observation sequences: The mhsmm package for R

Author keywords

Duration density; EM algorithm; Hidden markov model; R; Sojourn time; Viterbi algorithm

Indexed keywords


EID: 79952970127     PISSN: 15487660     EISSN: 15487660     Source Type: Journal    
DOI: 10.18637/jss.v039.i04     Document Type: Article
Times cited : (56)

References (15)
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    • The Viterbi algorithm
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    • Forney, G.D.1
  • 9
    • 0141907306 scopus 로고    scopus 로고
    • Estimating hidden Semi-Markov chains from discrete sequences
    • Guédon Y (2003). "Estimating Hidden Semi-Markov Chains from Discrete Sequences". Journal of Computational and Graphical Statistics, 12(3), 604-639.
    • (2003) Journal of Computational and Graphical Statistics , vol.12 , Issue.3 , pp. 604-639
    • Guédon, Y.1
  • 10
    • 77949289984 scopus 로고    scopus 로고
    • Quantifying degree of Mastitis from common trends in a panel of indicators for Mastitis in dairy cows
    • Højsgaard S, Friggens NC (2010). "Quantifying Degree of Mastitis from Common Trends in a Panel of Indicators for Mastitis in Dairy Cows". Journal of Dairy Science, 93(2), 582-592.
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    • Højsgaard, S.1    Friggens, N.C.2
  • 12
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    • A hidden Markov Model that finds genes in E. coli DNA
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    • (1994) Nucleic Acids Research , vol.22 , Issue.22 , pp. 4768-4778
    • Krogh, A.1    Mian, I.S.2    Haussler, D.3
  • 14
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    • A tutorial on hidden Markov models and selected applications in speech recognition
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    • R Development Core Team, R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.