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Volumn 22, Issue 2, 2005, Pages 203-219

Clustering univariate observations via mixtures of unimodal normal mixtures

Author keywords

Bayesian information criterion; Constrained maximization; Density estimation; EM algorithm

Indexed keywords


EID: 33744756623     PISSN: 01764268     EISSN: 14321343     Source Type: Journal    
DOI: 10.1007/s00357-005-0014-7     Document Type: Article
Times cited : (12)

References (16)
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  • 3
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  • 5
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    • Gutierrez, R.G.1    Carroll, R.J.2    Wang, N.3    Lee, G.-H.4    Taylor, B.H.5
  • 6
    • 0036822874 scopus 로고    scopus 로고
    • Unimodal density estimation using Kernel methods
    • HALL, P., and HUANG, L.-S. (2002), "Unimodal Density Estimation Using Kernel Methods", Statistica Sinica, 12, 965-990.
    • (2002) Statistica Sinica , vol.12 , pp. 965-990
    • Hall, P.1    Huang, L.-S.2
  • 10
    • 0031510027 scopus 로고    scopus 로고
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  • 11
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    • A graphical technique for determining the number of components in a mixture of normals
    • ROEDER, K. (1994), "A Graphical Technique for Determining the Number of Components in a Mixture of Normals", Journal of the American Statistical Association, 89, 487-495.
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    • Roeder, K.1
  • 13
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    • Estimating the dimension of a model
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  • 14
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    • A reliable data-based bandwidth selection method for Kernel density estimation
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  • 16
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    • A bootstrap testing procedure for investigating the number of subpopulations
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    • Wong, M.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.