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Volumn 30, Issue 3, 2020, Pages 485-506

Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components

Author keywords

Factor analysis; MCMC; Mixture model; R package

Indexed keywords


EID: 85071717650     PISSN: 09603174     EISSN: 15731375     Source Type: Journal    
DOI: 10.1007/s11222-019-09891-z     Document Type: Article
Times cited : (8)

References (68)
  • 1
    • 1342309210 scopus 로고    scopus 로고
    • Parallel metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference
    • Altekar, G., Dwarkadas, S., Huelsenbeck, J.P., Ronquist, F.: Parallel metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference. Bioinformatics 20(3), 407–415 (2004). 10.1093/bioinformatics/btg427
    • (2004) Bioinformatics , vol.20 , Issue.3 , pp. 407-415
    • Altekar, G.1    Dwarkadas, S.2    Huelsenbeck, J.P.3    Ronquist, F.4
  • 3
    • 79957827711 scopus 로고    scopus 로고
    • Sparse Bayesian infinite factor models
    • Bhattacharya, A., Dunson, D.B.: Sparse Bayesian infinite factor models. Biometrika 98(2), 291–306 (2011)
    • (2011) Biometrika , vol.98 , Issue.2 , pp. 291-306
    • Bhattacharya, A.1    Dunson, D.B.2
  • 5
    • 2242491935 scopus 로고    scopus 로고
    • Computational and inferential difficulties with mixture posterior distributions
    • Celeux, G., Hurn, M., Robert, C.P.: Computational and inferential difficulties with mixture posterior distributions. J. Am. Stat. Assoc. 95(451), 957–970 (2000a). 10.1080/01621459.2000.10474285
    • (2000) J. Am. Stat. Assoc. , vol.95 , Issue.451 , pp. 957-970
    • Celeux, G.1    Hurn, M.2    Robert, C.P.3
  • 6
    • 2242491935 scopus 로고    scopus 로고
    • Computational and inferential difficulties with mixture posterior distributions
    • Celeux, G., Hurn, M., Robert, C.P.: Computational and inferential difficulties with mixture posterior distributions. J. Am. Stat. Assoc. 95(451), 957–970 (2000b)
    • (2000) J. Am. Stat. Assoc. , vol.95 , Issue.451 , pp. 957-970
    • Celeux, G.1    Hurn, M.2    Robert, C.P.3
  • 9
    • 33644514005 scopus 로고    scopus 로고
    • Multivariate mixtures of normals with unknown number of components
    • Dellaportas, P., Papageorgiou, I.: Multivariate mixtures of normals with unknown number of components. Stat. Comput. 16(1), 57–68 (2006)
    • (2006) Stat. Comput. , vol.16 , Issue.1 , pp. 57-68
    • Dellaportas, P.1    Papageorgiou, I.2
  • 10
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm (with discussion)
    • Dempster, A.P., Laird, N.M., Rubin, D.: Maximum likelihood from incomplete data via the EM algorithm (with discussion). J. R. Stat. Soc. B 39, 1–38 (1977)
    • (1977) J. R. Stat. Soc. B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.3
  • 11
    • 79961240792 scopus 로고    scopus 로고
    • Rcpp: seamless R and C++ integration
    • Eddelbuettel, D., François, R.: Rcpp: seamless R and C++ integration. J. Stat. Softw. 40(8), 1–18 (2011). 10.18637/jss.v040.i08
    • (2011) J. Stat. Softw. , vol.40 , Issue.8 , pp. 1-18
    • Eddelbuettel, D.1    François, R.2
  • 12
    • 84889084625 scopus 로고    scopus 로고
    • Rcpparmadillo: accelerating R with high-performance C++ linear algebra
    • Eddelbuettel, D., Sanderson, C.: Rcpparmadillo: accelerating R with high-performance C++ linear algebra. Comput. Stat. Data Anal. 71, 1054–1063 (2014). 10.1016/j.csda.2013.02.005
    • (2014) Comput. Stat. Data Anal. , vol.71 , pp. 1054-1063
    • Eddelbuettel, D.1    Sanderson, C.2
  • 13
    • 0001120413 scopus 로고
    • A Bayesian analysis of some nonparametric problems
    • Ferguson, T.S.: A Bayesian analysis of some nonparametric problems. Ann. Stat. 1(2), 209–230 (1973)
    • (1973) Ann. Stat. , vol.1 , Issue.2 , pp. 209-230
    • Ferguson, T.S.1
  • 14
    • 0037262840 scopus 로고    scopus 로고
    • Mixtures of factor analysers. Bayesian estimation and inference by stochastic simulation
    • Fokoué, E., Titterington, D.: Mixtures of factor analysers. Bayesian estimation and inference by stochastic simulation. Mach. Learn. 50(1), 73–94 (2003)
    • (2003) Mach. Learn. , vol.50 , Issue.1 , pp. 73-94
    • Fokoué, E.1    Titterington, D.2
  • 15
    • 0001757440 scopus 로고
    • Multivariate data analysis as a discriminating method of the origin of wines
    • Forina, M., Armanino, C., Castino, M., Ubigli, M.: Multivariate data analysis as a discriminating method of the origin of wines. Vitis 25(3), 189–201 (1986)
    • (1986) Vitis , vol.25 , Issue.3 , pp. 189-201
    • Forina, M.1    Armanino, C.2    Castino, M.3    Ubigli, M.4
  • 16
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering, discriminant analysis and density estimation
    • Fraley, C., Raftery, A.E.: Model-based clustering, discriminant analysis and density estimation. J. Am. Stat. Assoc. 97, 611–631 (2002)
    • (2002) J. Am. Stat. Assoc. , vol.97 , pp. 611-631
    • Fraley, C.1    Raftery, A.E.2
  • 17
    • 85064009409 scopus 로고    scopus 로고
    • From here to infinity: sparse finite versus Dirichlet process mixtures in model based clustering
    • Frühwirth-Schnatter, S., Malsiner-Walli, G.: From here to infinity: sparse finite versus Dirichlet process mixtures in model based clustering. Adv. Data Anal. Classif. 13, 33–64 (2019)
    • (2019) Adv. Data Anal. Classif. , vol.13 , pp. 33-64
    • Frühwirth-Schnatter, S.1    Malsiner-Walli, G.2
  • 19
    • 84950453304 scopus 로고
    • Sampling-based approaches to calculating marginal densities
    • Gelfand, A., Smith, A.: Sampling-based approaches to calculating marginal densities. J. Am. Stat. Assoc. 85, 398–409 (1990)
    • (1990) J. Am. Stat. Assoc. , vol.85 , pp. 398-409
    • Gelfand, A.1    Smith, A.2
  • 20
    • 0021518209 scopus 로고
    • Stochastic relaxation, gibbs distributions, and the Bayesian restoration of images
    • Geman, S., Geman, D.: Stochastic relaxation, gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Mach. Intell. PAMI–6(6), 721–741 (1984). 10.1109/TPAMI.1984.4767596
    • (1984) IEEE Trans. Pattern Anal. Mach. Intell. , vol.PAMI–6 , Issue.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 21
    • 0030539706 scopus 로고    scopus 로고
    • Measuring the pricing error of the arbitrage pricing theory
    • Geweke, J., Zhou, G.: Measuring the pricing error of the arbitrage pricing theory. Rev. Financ. Stud. 9(2), 557–587 (1996). 10.1093/rfs/9.2.557
    • (1996) Rev. Financ. Stud. , vol.9 , Issue.2 , pp. 557-587
    • Geweke, J.1    Zhou, G.2
  • 23
    • 84950437936 scopus 로고
    • Annealing Markov chain Monte Carlo with applications to ancestral inference
    • Geyer, C.J., Thompson, E.A.: Annealing Markov chain Monte Carlo with applications to ancestral inference. J. Am. Stat. Assoc. 90(431), 909–920 (1995). 10.1080/01621459.1995.10476590
    • (1995) J. Am. Stat. Assoc. , vol.90 , Issue.431 , pp. 909-920
    • Geyer, C.J.1    Thompson, E.A.2
  • 25
    • 77956889087 scopus 로고
    • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    • Green, P.J.: Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82(4), 711–732 (1995)
    • (1995) Biometrika , vol.82 , Issue.4 , pp. 711-732
    • Green, P.J.1
  • 26
    • 0024682770 scopus 로고
    • Updating the inverse of a matrix
    • Hager, W.W.: Updating the inverse of a matrix. SIAM Rev. 31(2), 221–239 (1989)
    • (1989) SIAM Rev. , vol.31 , Issue.2 , pp. 221-239
    • Hager, W.W.1
  • 27
    • 0030305457 scopus 로고    scopus 로고
    • R: a language for data analysis and graphics
    • Ihaka, R., Gentleman, R.: R: a language for data analysis and graphics. J. Comput. Graph. Stat. 5(3), 299–314 (1996). 10.1080/10618600.1996.10474713
    • (1996) J. Comput. Graph. Stat. , vol.5 , Issue.3 , pp. 299-314
    • Ihaka, R.1    Gentleman, R.2
  • 29
    • 0001926319 scopus 로고
    • On the rank of the reduced correlational matrix in multiple-factor analysis
    • Ledermann, W.: On the rank of the reduced correlational matrix in multiple-factor analysis. Psychometrika 2(2), 85–93 (1937)
    • (1937) Psychometrika , vol.2 , Issue.2 , pp. 85-93
    • Ledermann, W.1
  • 31
    • 85027933784 scopus 로고    scopus 로고
    • Model-based clustering based on sparse finite Gaussian mixtures
    • Malsiner Walli, G., Frühwirth-Schnatter, S., Grün, B.: Model-based clustering based on sparse finite Gaussian mixtures. Stat. Comput. 26, 303–324 (2016)
    • (2016) Stat. Comput. , vol.26 , pp. 303-324
    • Malsiner Walli, G.1    Frühwirth-Schnatter, S.2    Grün, B.3
  • 33
    • 33750274518 scopus 로고    scopus 로고
    • Bayesian modelling and inference on mixtures of distributions
    • Marin, J., Mengersen, K., Robert, C.: Bayesian modelling and inference on mixtures of distributions. Handb. Stat. 25(1), 577–590 (2005)
    • (2005) Handb. Stat. , vol.25 , Issue.1 , pp. 577-590
    • Marin, J.1    Mengersen, K.2    Robert, C.3
  • 34
    • 84897617724 scopus 로고    scopus 로고
    • Stochastic search item selection for factor analytic models
    • Mavridis, D., Ntzoufras, I.: Stochastic search item selection for factor analytic models. Br. J. Math. Stat. Psychol. 67(2), 284–303 (2014). 10.1111/bmsp.12019
    • (2014) Br. J. Math. Stat. Psychol. , vol.67 , Issue.2 , pp. 284-303
    • Mavridis, D.1    Ntzoufras, I.2
  • 38
    • 45449088666 scopus 로고    scopus 로고
    • Parsimonious Gaussian mixture models
    • McNicholas, P.D., Murphy, T.B.: Parsimonious Gaussian mixture models. Stat. Comput. 18(3), 285–296 (2008)
    • (2008) Stat. Comput. , vol.18 , Issue.3 , pp. 285-296
    • McNicholas, P.D.1    Murphy, T.B.2
  • 39
    • 77958504829 scopus 로고    scopus 로고
    • Model-based clustering of microarray expression data via latent Gaussian mixture models
    • McNicholas, P.D., Murphy, T.B.: Model-based clustering of microarray expression data via latent Gaussian mixture models. Bioinformatics 26(21), 2705 (2010)
    • (2010) Bioinformatics , vol.26 , Issue.21 , pp. 2705
    • McNicholas, P.D.1    Murphy, T.B.2
  • 40
    • 70549109507 scopus 로고    scopus 로고
    • Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models
    • McNicholas, P.D., Murphy, T.B., McDaid, A.F., Frost, D.: Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models. Comput. Stat. Data Anal. 54(3), 711–723 (2010)
    • (2010) Comput. Stat. Data Anal. , vol.54 , Issue.3 , pp. 711-723
    • McNicholas, P.D.1    Murphy, T.B.2    McDaid, A.F.3    Frost, D.4
  • 41
    • 85021739344 scopus 로고    scopus 로고
    • Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data
    • McParland, D., Phillips, C.M., Brennan, L., Roche, H.M., Gormley, I.C.: Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data. Stat. Med. 36(28), 4548–4569 (2017)
    • (2017) Stat. Med. , vol.36 , Issue.28 , pp. 4548-4569
    • McParland, D.1    Phillips, C.M.2    Brennan, L.3    Roche, H.M.4    Gormley, I.C.5
  • 42
    • 18244387717 scopus 로고    scopus 로고
    • The EM algorithm—an old folk-song sung to a fast new tune
    • Meng, X.L., Van Dyk, D.: The EM algorithm—an old folk-song sung to a fast new tune. J. R. Stat. Soc. Ser. B (Stat. Methodol.) 59(3), 511–567 (1997)
    • (1997) J. R. Stat. Soc. Ser. B (Stat. Methodol.) , vol.59 , Issue.3 , pp. 511-567
    • Meng, X.L.1    Van Dyk, D.2
  • 44
    • 77950032550 scopus 로고    scopus 로고
    • Markov chain sampling methods for Dirichlet process mixture models
    • Neal, R.M.: Markov chain sampling methods for Dirichlet process mixture models. J. Comput. Graph. Stat. 9(2), 249–265 (2000)
    • (2000) J. Comput. Graph. Stat. , vol.9 , Issue.2 , pp. 249-265
    • Neal, R.M.1
  • 45
    • 34249673263 scopus 로고    scopus 로고
    • Bayesian finite mixtures with an unknown number of components: the allocation sampler
    • Nobile, A., Fearnside, A.T.: Bayesian finite mixtures with an unknown number of components: the allocation sampler. Stat. Comput. 17(2), 147–162 (2007). 10.1007/s11222-006-9014-7
    • (2007) Stat. Comput. , vol.17 , Issue.2 , pp. 147-162
    • Nobile, A.1    Fearnside, A.T.2
  • 47
    • 84887047429 scopus 로고    scopus 로고
    • Handling the label switching problem in latent class models via the ECR algorithm
    • Papastamoulis, P.: Handling the label switching problem in latent class models via the ECR algorithm. Commun. Stat. Simul. Comput. 43(4), 913–927 (2014)
    • (2014) Commun. Stat. Simul. Comput. , vol.43 , Issue.4 , pp. 913-927
    • Papastamoulis, P.1
  • 48
    • 84956900027 scopus 로고    scopus 로고
    • label.switching: an R package for dealing with the label switching problem in MCMC outputs
    • Papastamoulis, P.: label.switching: an R package for dealing with the label switching problem in MCMC outputs. J. Stat. Softw. 69(1), 1–24 (2016)
    • (2016) J. Stat. Softw. , vol.69 , Issue.1 , pp. 1-24
    • Papastamoulis, P.1
  • 49
    • 85044919583 scopus 로고    scopus 로고
    • Overfitting Bayesian mixtures of factor analyzers with an unknown number of components
    • Papastamoulis, P.: Overfitting Bayesian mixtures of factor analyzers with an unknown number of components. Comput. Stat. Data Anal. 124, 220–234 (2018b). 10.1016/j.csda.2018.03.007
    • (2018) Comput. Stat. Data Anal. , vol.124 , pp. 220-234
    • Papastamoulis, P.1
  • 50
    • 58549097308 scopus 로고    scopus 로고
    • Reversible jump MCMC in mixtures of normal distributions with the same component means
    • Papastamoulis, P., Iliopoulos, G.: Reversible jump MCMC in mixtures of normal distributions with the same component means. Comput. Stat. Data Anal. 53(4), 900–911 (2009)
    • (2009) Comput. Stat. Data Anal. , vol.53 , Issue.4 , pp. 900-911
    • Papastamoulis, P.1    Iliopoulos, G.2
  • 51
    • 77956665562 scopus 로고    scopus 로고
    • An artificial allocations based solution to the label switching problem in Bayesian analysis of mixtures of distributions
    • Papastamoulis, P., Iliopoulos, G.: An artificial allocations based solution to the label switching problem in Bayesian analysis of mixtures of distributions. J. Comput. Graph. Stat. 19, 313–331 (2010)
    • (2010) J. Comput. Graph. Stat. , vol.19 , pp. 313-331
    • Papastamoulis, P.1    Iliopoulos, G.2
  • 52
    • 84876687117 scopus 로고    scopus 로고
    • On the convergence rate of random permutation sampler and ECR algorithm in missing data models
    • Papastamoulis, P., Iliopoulos, G.: On the convergence rate of random permutation sampler and ECR algorithm in missing data models. Methodol. Comput. Appl. Probab. 15(2), 293–304 (2013). 10.1007/s11009-011-9238-7
    • (2013) Methodol. Comput. Appl. Probab. , vol.15 , Issue.2 , pp. 293-304
    • Papastamoulis, P.1    Iliopoulos, G.2
  • 53
    • 85021434863 scopus 로고    scopus 로고
    • BayesBinMix: an R package for model based clustering of multivariate binary data
    • Papastamoulis, P., Rattray, M.: BayesBinMix: an R package for model based clustering of multivariate binary data. R J. 9(1), 403–420 (2017)
    • (2017) R J. , vol.9 , Issue.1 , pp. 403-420
    • Papastamoulis, P.1    Rattray, M.2
  • 54
    • 41149087694 scopus 로고    scopus 로고
    • CODA: convergence diagnosis and output analysis for MCMC
    • Plummer, M., Best, N., Cowles, K., Vines, K.: CODA: convergence diagnosis and output analysis for MCMC. R News 6(1), 7–11 (2006)
    • (2006) R News , vol.6 , Issue.1 , pp. 7-11
    • Plummer, M.1    Best, N.2    Cowles, K.3    Vines, K.4
  • 55
    • 84863304598 scopus 로고    scopus 로고
    • R Foundation for Statistical Computing, Vienna, Austria, 3-900051-07-0
    • R Core Team (2016) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/, ISBN 3-900051-07-0
    • (2016) R: A Language and Environment for Statistical Computing
  • 56
    • 84950632109 scopus 로고
    • Objective criteria for the evaluation of clustering methods
    • Rand, W.M.: Objective criteria for the evaluation of clustering methods. J. Am. Stat. Assoc. 66(336), 846–850 (1971)
    • (1971) J. Am. Stat. Assoc. , vol.66 , Issue.336 , pp. 846-850
    • Rand, W.M.1
  • 57
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and the EM algorithm
    • Redner, R.A., Walker, H.F.: Mixture densities, maximum likelihood and the EM algorithm. SIAM Rev. 26(2), 195–239 (1984)
    • (1984) SIAM Rev. , vol.26 , Issue.2 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2
  • 58
    • 84953731160 scopus 로고    scopus 로고
    • r package version 1.4.2
    • Revolution Analytics and Steve Weston (2014) foreach: Foreach looping construct for R. http://CRAN.R-project.org/package=foreach, r package version 1.4.2
    • (2014) Foreach: Foreach Looping Construct for R
  • 60
    • 18244378520 scopus 로고    scopus 로고
    • On Bayesian analysis of mixtures with an unknown number of components
    • Richardson, S., Green, P.J.: On Bayesian analysis of mixtures with an unknown number of components. J. R. Stat. Soc. Ser. B 59(4), 731–758 (1997)
    • (1997) J. R. Stat. Soc. Ser. B , vol.59 , Issue.4 , pp. 731-758
    • Richardson, S.1    Green, P.J.2
  • 61
    • 80054736950 scopus 로고    scopus 로고
    • Asymptotic behaviour of the posterior distribution in overfitted mixture models
    • Rousseau, J., Mengersen, K.: Asymptotic behaviour of the posterior distribution in overfitted mixture models. J. R. Stat. Soc. Ser. B (Stat. Methodol.) 73(5), 689–710 (2011)
    • (2011) J. R. Stat. Soc. Ser. B (Stat. Methodol.) , vol.73 , Issue.5 , pp. 689-710
    • Rousseau, J.1    Mengersen, K.2
  • 62
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz, G.: Estimating the dimension of a model. Ann. Stat. 6(2), 461–464 (1978)
    • (1978) Ann. Stat. , vol.6 , Issue.2 , pp. 461-464
    • Schwarz, G.1
  • 63
    • 85062590812 scopus 로고    scopus 로고
    • mclust 5: clustering, classification and density estimation using Gaussian finite mixture models
    • Scrucca, L., Fop, M., Murphy, T.B., Raftery, A.E.: mclust 5: clustering, classification and density estimation using Gaussian finite mixture models. R J. 8(1), 205–233 (2017)
    • (2017) R J. , vol.8 , Issue.1 , pp. 205-233
    • Scrucca, L.1    Fop, M.2    Murphy, T.B.3    Raftery, A.E.4
  • 64
    • 0034374610 scopus 로고    scopus 로고
    • Bayesian analysis of mixture models with an unknown number of components—an alternative to reversible jump methods
    • Stephens, M.: Bayesian analysis of mixture models with an unknown number of components—an alternative to reversible jump methods. Ann. Stat. 28(1), 40–74 (2000)
    • (2000) Ann. Stat. , vol.28 , Issue.1 , pp. 40-74
    • Stephens, M.1
  • 65
    • 32644447558 scopus 로고
    • Der heutige stand der kaffeechemie
    • Association Scientifique International du Cafe, Bogata, Columbia
    • Streuli, H.: Der heutige stand der kaffeechemie. In: 6th International Colloquium on Coffee Chemisrty, Association Scientifique International du Cafe, Bogata, Columbia, pp. 61–72 (1973)
    • (1973) 6Th International Colloquium on Coffee Chemisrty , pp. 61-72
    • Streuli, H.1
  • 66
    • 0033556788 scopus 로고    scopus 로고
    • Mixtures of probabilistic principal component analyzers
    • Tipping, M.E., Bishop, C.M.: Mixtures of probabilistic principal component analyzers. Neural Comput. 11(2), 443–482 (1999)
    • (1999) Neural Comput. , vol.11 , Issue.2 , pp. 443-482
    • Tipping, M.E.1    Bishop, C.M.2
  • 67
    • 84941350322 scopus 로고    scopus 로고
    • Overfitting Bayesian mixture models with an unknown number of components
    • van Havre, Z., White, N., Rousseau, J., Mengersen, K.: Overfitting Bayesian mixture models with an unknown number of components. PLoS ONE 10(7), 1–27 (2015)
    • (2015) PLoS ONE , vol.10 , Issue.7 , pp. 1-27
    • van Havre, Z.1    White, N.2    Rousseau, J.3    Mengersen, K.4
  • 68
    • 0034782618 scopus 로고    scopus 로고
    • Model-based clustering and data transformations for gene expression data
    • Yeung, K.Y., Fraley, C., Murua, A., Raftery, A.E., Ruzzo, W.L.: Model-based clustering and data transformations for gene expression data. Bioinformatics 17(10), 977–987 (2001). 10.1093/bioinformatics/17.10.977
    • (2001) Bioinformatics , vol.17 , Issue.10 , pp. 977-987
    • Yeung, K.Y.1    Fraley, C.2    Murua, A.3    Raftery, A.E.4    Ruzzo, W.L.5


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