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Volumn 47, Issue , 2012, Pages

High-dimensional Bayesian clustering with variable selection: The R package bclust

Author keywords

Agglomerative clustering; Bayesian clustering; Bayesian variable selection; Dendrogram; Hierarchical clustering; R; Spike and slab model

Indexed keywords


EID: 84863314336     PISSN: None     EISSN: 15487660     Source Type: Journal    
DOI: 10.18637/jss.v047.i05     Document Type: Article
Times cited : (25)

References (38)
  • 1
    • 34548536094 scopus 로고    scopus 로고
    • The High-Dimension, Low-Sample-Size Geometric Representation Holds Under Mild Conditions
    • Ahn J, Marron JS, Muller KM, Chi YY (2007). The High-Dimension, Low-Sample-Size Geometric Representation Holds Under Mild Conditions. Biometrika, 94(3), 760-766.
    • (2007) Biometrika , vol.94 , Issue.3 , pp. 760-766
    • Ahn, J.1    Marron, J.S.2    Muller, K.M.3    Chi, Y.Y.4
  • 3
    • 84857383225 scopus 로고    scopus 로고
    • HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data
    • Bergé L, Bouveyron C, Girard S (2012). HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data. Journal of Statistical Software, 46(6), 1-29. URL http://www.jstatsoft.org/v46/i06/.
    • (2012) Journal of Statistical Software , vol.46 , Issue.6 , pp. 1-29
    • Bergé, L.1    Bouveyron, C.2    Girard, S.3
  • 5
    • 33749626257 scopus 로고    scopus 로고
    • A Laplace Mixture Model for Identification of Differential Expression in Microarray Experiments
    • Bhowmick D, Davison AC, Goldstein DR, Ruffieux Y (2006). A Laplace Mixture Model for Identification of Differential Expression in Microarray Experiments. Biostatistics, 7, 630-641.
    • (2006) Biostatistics , vol.7 , pp. 630-641
    • Bhowmick, D.1    Davison, A.C.2    Goldstein, D.R.3    Ruffieux, Y.4
  • 6
    • 39849102639 scopus 로고    scopus 로고
    • Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR
    • Bondell HD, Reich BJ (2008). Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR. Biometrics, 64, 115-123.
    • (2008) Biometrics , vol.64 , pp. 115-123
    • Bondell, H.D.1    Reich, B.J.2
  • 8
    • 0020998698 scopus 로고
    • On Using Principal Components Before Separating a Mixture of Two Multivariate Normal Distributions
    • Chang WC (1983). On Using Principal Components Before Separating a Mixture of Two Multivariate Normal Distributions. Applied Statistics, 32, 267-275.
    • (1983) Applied Statistics , vol.32 , pp. 267-275
    • Chang, W.C.1
  • 14
    • 0031526204 scopus 로고    scopus 로고
    • Approaches for Bayesian Variable Selection
    • George EI, McCulloch RE (1997). Approaches for Bayesian Variable Selection. Statistica Sinica, 7, 339-373.
    • (1997) Statistica Sinica , vol.7 , pp. 339-373
    • George, E.I.1    McCulloch, R.E.2
  • 15
    • 0036188158 scopus 로고    scopus 로고
    • Mixture Modelling of Gene Expression Data From Microarray Experiments
    • Ghosh D, Chinnaiyan AM (2002). Mixture Modelling of Gene Expression Data From Microarray Experiments. Bioinformatics, 18, 275-286.
    • (2002) Bioinformatics , vol.18 , pp. 275-286
    • Ghosh, D.1    Chinnaiyan, A.M.2
  • 17
    • 33645507298 scopus 로고    scopus 로고
    • A Quantitative Study of Gene Regulation Involved in the Immune Response of Anopheline Mosquitoes: An Application of Bayesian Hierarchical Clustering of Curves
    • Heard NA, Holmes CC, Stephens DA (2006). A Quantitative Study of Gene Regulation Involved in the Immune Response of Anopheline Mosquitoes: An Application of Bayesian Hierarchical Clustering of Curves. Journal of the American Statistical Association, 101, 18-29.
    • (2006) Journal of the American Statistical Association , vol.101 , pp. 18-29
    • Heard, N.A.1    Holmes, C.C.2    Stephens, D.A.3
  • 18
    • 33645992615 scopus 로고    scopus 로고
    • Model-Based Subspace Clustering
    • Hoff PD (2006). Model-Based Subspace Clustering. Bayesian Analysis, 1, 321-344.
    • (2006) Bayesian Analysis , vol.1 , pp. 321-344
    • Hoff, P.D.1
  • 20
    • 33845734547 scopus 로고    scopus 로고
    • Variable Selection in Clustering via Dirichlet Process Mixture Models
    • Kim S, Tadesse MG, Vannucci M (2006). Variable Selection in Clustering via Dirichlet Process Mixture Models. Biometrika, 93, 877-893.
    • (2006) Biometrika , vol.93 , pp. 877-893
    • Kim, S.1    Tadesse, M.G.2    Vannucci, M.3
  • 21
    • 0003126317 scopus 로고
    • A General Theory of Classificatory Sorting Strategies 1. Hierarchical Systems
    • Lance GN, Williams WT (1967). A General Theory of Classificatory Sorting Strategies 1. Hierarchical Systems. The Computer Journal, 9, 373-380.
    • (1967) The Computer Journal , vol.9 , pp. 373-380
    • Lance, G.N.1    Williams, W.T.2
  • 22
    • 77956878238 scopus 로고    scopus 로고
    • Neighborhood Graphs, Stripes and Shadow Plots for Cluster Visualization
    • Leisch F (2010). Neighborhood Graphs, Stripes and Shadow Plots for Cluster Visualization. Statistics and Computing, 20, 457-469.
    • (2010) Statistics and Computing , vol.20 , pp. 457-469
    • Leisch, F.1
  • 25
    • 0036203115 scopus 로고    scopus 로고
    • A Mixture Model-Based Approach to the Clustering of Microarray Expression Data
    • McLachlan GJ, Bean RW, Peel D (2002). A Mixture Model-Based Approach to the Clustering of Microarray Expression Data. Bioinformatics, 18, 413-422.
    • (2002) Bioinformatics , vol.18 , pp. 413-422
    • McLachlan, G.J.1    Bean, R.W.2    Peel, D.3
  • 28
    • 1042304216 scopus 로고    scopus 로고
    • ape: Analyses of Phylogenetics and Evolution in R Language
    • Paradis E, Claude J, Strimmer K (2004). ape: Analyses of Phylogenetics and Evolution in R Language. Bioinformatics, 20, 289-290.
    • (2004) Bioinformatics , vol.20 , pp. 289-290
    • Paradis, E.1    Claude, J.2    Strimmer, K.3
  • 32
    • 84863304598 scopus 로고    scopus 로고
    • R Development Core Team R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0
    • R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/.
    • (2012) R: A Language and Environment For Statistical Computing
  • 36
    • 43749096785 scopus 로고    scopus 로고
    • Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data
    • Wang S, Zhu J (2008). Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data. Biometrics, 64, 440-448.
    • (2008) Biometrics , vol.64 , pp. 440-448
    • Wang, S.1    Zhu, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.