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Volumn , Issue , 2008, Pages 373-383

Latent classes of objects and variable selection

Author keywords

Factor analysis; Finite Gaussian mixtures; LASSO

Indexed keywords

FACTOR ANALYSIS;

EID: 84904005970     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-7908-2084-3_31     Document Type: Conference Paper
Times cited : (4)

References (16)
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    • Banfield, J.D.1    Raftery, A.E.2
  • 3
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • FAN, J. and LI, R. (2001): Variable selection via nonconcave penalized likelihood and its oracle properties, Journal of the American Statistical Association, 96, 1348-1360.
    • (2001) Journal of the American Statistical Association , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 4
    • 22844453564 scopus 로고    scopus 로고
    • MCLUST: Software for model-based cluster analysis
    • FRALEY, C. and RAFTERY, A.E. (1999): MCLUST: Software for model-based cluster analysis, Journal of Classification, 16, 297-206.
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    • Fraley, C.1    Raftery, A.E.2
  • 5
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    • 0242291493 scopus 로고    scopus 로고
    • MCLUST: Software for model-based clustering, discriminant analysis, and density estimation
    • Department of Statistics, University of Washington
    • FRALEY, C. and RAFTERY, A.E. (2002b): MCLUST: Software for model-based clustering, discriminant analysis, and density estimation, Technical Report No. 415, Department of Statistics, University of Washington.
    • (2002) Technical Report No. 415
    • Fraley, C.1    Raftery, A.E.2
  • 7
    • 0742306126 scopus 로고    scopus 로고
    • Enhanced software for model-based clustering, discriminant analysis, and density estimation: MCLUST
    • FRALEY, C. and RAFTERY, A.E. (2003): Enhanced Software for model-based clustering, discriminant analysis, and density estimation: MCLUST, Journal of Classification, 20, 263-286.
    • (2003) Journal of Classification , vol.20 , pp. 263-286
    • Fraley, C.1    Raftery, A.E.2
  • 8
    • 33644863012 scopus 로고    scopus 로고
    • Subset clustering of binary sequences, with an application to genomic Abnormality data
    • HOFF, P.D. (2005): Subset clustering of binary sequences, with an application to genomic abnormality data, Biometrics, 61, 1027-1036.
    • (2005) Biometrics , vol.61 , pp. 1027-1036
    • Hoff, P.D.1
  • 9
    • 26444617168 scopus 로고    scopus 로고
    • Variable selection using MM algorithms
    • HUNTER, D.R. and LI, R. (2005): Variable selection using MM algorithms, The Annals of Statistics, 33, 1617-1642.
    • (2005) The Annals of Statistics , vol.33 , pp. 1617-1642
    • Hunter, D.R.1    Li, R.2
  • 11
    • 15044339834 scopus 로고    scopus 로고
    • Bayesian clustering with variable and transformation selection (with discussion)
    • LIU, J.S., ZHANG, J.L., PALUMBO, M.J. and LAWRENCE, C.E. (2003): Bayesian clustering with variable and transformation selection (with discussion), Bayesian Statistics, 7, 249-275.
    • (2003) Bayesian Statistics , vol.7 , pp. 249-275
    • Liu, J.S.1    Zhang, J.L.2    Palumbo, M.J.3    Lawrence, C.E.4
  • 14
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    • Penalized model-based clustering with application to variable selection
    • PAN, W., and SHEN, X. (2007): Penalized model-based clustering with application to variable selection Journal fo machine learning research, 8, 1145-1164.
    • (2007) Journal Fo Machine Learning Research , vol.8 , pp. 1145-1164
    • Pan, W.1    Shen, X.2
  • 15
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    • Estimating the dimension of a model
    • SCHWARZ, G. (1978): Estimating the Dimension of a Model, Annals of Statistics, 6, 461-464.
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    • Schwarz, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.