메뉴 건너뛰기




Volumn 39, Issue 11, 2012, Pages 2363-2377

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

Author keywords

Clustering; Dirichlet process mixture; Parkinson's disease; UPDRS

Indexed keywords


EID: 84868112663     PISSN: 02664763     EISSN: 13600532     Source Type: Journal    
DOI: 10.1080/02664763.2012.710897     Document Type: Article
Times cited : (5)

References (61)
  • 1
    • 0000708831 scopus 로고
    • Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
    • C.E. Antoniak, Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems, Ann. Stat. 2 (1974), pp. 1152-1174.
    • (1974) Ann. Stat , vol.2 , pp. 1152-1174
    • Antoniak, C.E.1
  • 2
    • 85042555546 scopus 로고
    • Bayesian cluster analysis
    • D.A. Binder, Bayesian cluster analysis, Biometrika 65 (1978), pp. 31-38.
    • (1978) Biometrika , vol.65 , pp. 31-38
    • Binder, D.A.1
  • 3
    • 0001203039 scopus 로고
    • Discreteness of Ferguson selections
    • D. Blackwell, Discreteness of Ferguson selections, Ann. Stat. 1 (1973), pp. 356-358.
    • (1973) Ann. Stat , vol.1 , pp. 356-358
    • Blackwell, D.1
  • 4
    • 0002617436 scopus 로고
    • Ferguson distributions via Pólya urn schemes
    • D. Blackwell and J.B. MacQueen, Ferguson distributions via Pólya urn schemes, Ann. Stat. 1 (1973), pp. 353-355.
    • (1973) Ann. Stat , vol.1 , pp. 353-355
    • Blackwell, D.1    Macqueen, J.B.2
  • 5
    • 84867186048 scopus 로고    scopus 로고
    • Variational inference for Dirichlet process mixtures
    • D.M. Blei and M.I. Jordan, Variational inference for Dirichlet process mixtures, Bayesian Anal. 1 (2006), pp. 121-144.
    • (2006) Bayesian Anal , vol.1 , pp. 121-144
    • Blei, D.M.1    Jordan, M.I.2
  • 6
    • 2242491935 scopus 로고    scopus 로고
    • Computational and inferential difficulties with mixture posterior distributions
    • G. Celeux, M. Hurn, and C.P. Robert, Computational and inferential difficulties with mixture posterior distributions, J. Am. Statist. Assoc. 95 (2000), pp. 957-970.
    • (2000) J. Am. Statist. Assoc , vol.95 , pp. 957-970
    • Celeux, G.1    Hurn, M.2    Robert, C.P.3
  • 8
    • 33845756481 scopus 로고    scopus 로고
    • Model-based clustering for expression data via a Dirichlet process mixture model
    • K.A. Do, P. Müller, and M. Vannucci, eds., Cambridge University Press. Cambridge
    • D.B. Dahl, Model-based clustering for expression data via a Dirichlet process mixture model, in Bayesian Inference for Gene Expression and Proteomics, K.A. Do, P. Müller, and M. Vannucci, eds., Cambridge University Press. Cambridge, 2006, pp. 201-218.
    • (2006) Bayesian Inference For Gene Expression and Proteomics , pp. 201-218
    • Dahl, D.B.1
  • 10
    • 21344479762 scopus 로고
    • Estimating normal means with a Dirichlet process prior
    • M.D. Escobar, Estimating normal means with a Dirichlet process prior, J.Am. Statist.Assoc. 89 (1994), pp. 268-277.
    • (1994) J.Am. Statist.Assoc , vol.89 , pp. 268-277
    • Escobar, M.D.1
  • 11
    • 84950937290 scopus 로고
    • Bayesian density estimation and inference using mixtures
    • M.D. Escobar and M. West, Bayesian density estimation and inference using mixtures, J. Am. Statist. Assoc. 90 (1995), pp. 577-588.
    • (1995) J. Am. Statist. Assoc , vol.90 , pp. 577-588
    • Escobar, M.D.1    West, M.2
  • 12
    • 0001120413 scopus 로고
    • A Bayesian analysis of some nonparametric problems
    • T.S. Ferguson, A Bayesian analysis of some nonparametric problems, Ann. Stat. 1 (1973), pp. 209-230.
    • (1973) Ann. Stat , vol.1 , pp. 209-230
    • Ferguson, T.S.1
  • 13
    • 0036169364 scopus 로고    scopus 로고
    • The heterogeneity of idiopathic Parkinson's disease
    • T. Foltynie, C. Brayne, and R.A. Barker, The heterogeneity of idiopathic Parkinson's disease, J. Neurol. 249 (2002), pp. 138-145.
    • (2002) J. Neurol , vol.249 , pp. 138-145
    • Foltynie, T.1    Brayne, C.2    Barker, R.A.3
  • 14
    • 77954199057 scopus 로고    scopus 로고
    • Improved criteria for clustering based on the posterior similarity matrix
    • A. Fritsch and K. Ickstadt, Improved criteria for clustering based on the posterior similarity matrix, Bayesian Anal. 4 (2009), pp. 367-392.
    • (2009) Bayesian Anal , vol.4 , pp. 367-392
    • Fritsch, A.1    Ickstadt, K.2
  • 15
    • 1842815959 scopus 로고    scopus 로고
    • Markov chain Monte Carlo estimation of classical and dynamic switching and mixture models
    • S. Frühwirth-Schnatter, Markov chain Monte Carlo estimation of classical and dynamic switching and mixture models, J. Am. Statist. Assoc. 96 (2001), pp. 194-209.
    • (2001) J. Am. Statist. Assoc , vol.96 , pp. 194-209
    • Frühwirth-Schnatter, S.1
  • 18
    • 84893179575 scopus 로고
    • Variable selection via Gibbs sampling
    • E.I. George and R.E. McCulloch, Variable selection via Gibbs sampling, J.Am.Statist.Assoc. 88 (1993), pp. 881-889.
    • (1993) J.Am.Statist.Assoc , vol.88 , pp. 881-889
    • George, E.I.1    McCulloch, R.E.2
  • 19
    • 0035531242 scopus 로고    scopus 로고
    • Modelling heterogeneity with and without the Dirichlet process
    • P.J. Green and S. Richardson, Modelling heterogeneity with and without the Dirichlet process, Scand. J. Stat. 2 (2001), pp. 355-375.
    • (2001) Scand. J. Stat , vol.2 , pp. 355-375
    • Green, P.J.1    Richardson, S.2
  • 21
    • 1842816362 scopus 로고    scopus 로고
    • Gibbs sampling methods for stick-breaking priors
    • H. Ishwaran and L.F. James, Gibbs sampling methods for stick-breaking priors, J. Am. Statist. Assoc. 96 (2001), pp. 161-173.
    • (2001) J. Am. Statist. Assoc , vol.96 , pp. 161-173
    • Ishwaran, H.1    James, L.F.2
  • 22
    • 0036749869 scopus 로고    scopus 로고
    • Approximate Dirichlet process computing in finite normal mixtures: Smoothing and prior information
    • H. Ishwaran and L.F. James, Approximate Dirichlet process computing in finite normal mixtures: Smoothing and prior information, J. Comput. Graph. Stat. 11 (2002), pp. 508-532.
    • (2002) J. Comput. Graph. Stat , vol.11 , pp. 508-532
    • Ishwaran, H.1    James, L.F.2
  • 23
    • 0001677650 scopus 로고    scopus 로고
    • Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models
    • H. Ishwaran and M. Zarepour, Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models, Biometrika 87 (2000), pp. 371-390.
    • (2000) Biometrika , vol.87 , pp. 371-390
    • Ishwaran, H.1    Zarepour, M.2
  • 25
    • 1842486852 scopus 로고    scopus 로고
    • A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model
    • S. Jain and R.M. Neal, A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model, J. Comput. Graph. Stat. 13 (2004), pp. 158-182.
    • (2004) J. Comput. Graph. Stat , vol.13 , pp. 158-182
    • Jain, S.1    Neal, R.M.2
  • 26
    • 44649182304 scopus 로고    scopus 로고
    • Splitting and merging components of a nonconjugate Dirichlet process mixture model
    • S. Jain and R.M. Neal, Splitting and merging components of a nonconjugate Dirichlet process mixture model, Bayesian Anal. 2 (2007), pp. 445-472.
    • (2007) Bayesian Anal , vol.2 , pp. 445-472
    • Jain, S.1    Neal, R.M.2
  • 27
    • 0014129195 scopus 로고
    • Hierarchical clustering schemes
    • S.C. Johnson, Hierarchical clustering schemes, Psychometrika 32 (1967), pp. 241-254.
    • (1967) Psychometrika , vol.32 , pp. 241-254
    • Johnson, S.C.1
  • 29
    • 0031798932 scopus 로고    scopus 로고
    • The structure of psychosis: Latent class analysis of probands from the Roscommon family study
    • K.S. Kendler, L.M. Karkowski, and D. Walsh, The structure of psychosis: Latent class analysis of probands from the Roscommon family study, Arch. Gen. Psychiatry 55 (1998), pp. 492-509.
    • (1998) Arch. Gen. Psychiatry , vol.55 , pp. 492-509
    • Kendler, K.S.1    Karkowski, L.M.2    Walsh, D.3
  • 30
    • 33845734547 scopus 로고    scopus 로고
    • Variable selection in clustering via Dirichlet process mixture models
    • S. Kim, M.G. Tadesse, and M. Vannucci, Variable selection in clustering via Dirichlet process mixture models, Biometrika 93 (2006), pp. 877-893.
    • (2006) Biometrika , vol.93 , pp. 877-893
    • Kim, S.1    Tadesse, M.G.2    Vannucci, M.3
  • 31
    • 35348994521 scopus 로고    scopus 로고
    • Bayesian model-based clustering procedures
    • J.W. Lau and P.J. Green, Bayesian model-based clustering procedures, J. Comput. Graph. Stat. 16 (2007), pp. 526-558.
    • (2007) J. Comput. Graph. Stat , vol.16 , pp. 526-558
    • Lau, J.W.1    Green, P.J.2
  • 32
    • 72049132087 scopus 로고    scopus 로고
    • Beyond symptom dimensions: Schizophrenia risk factors for patient groups derived by latent class analysis
    • S. Leask, J. Vermunt, D. Done, T. Crow, M. Blows, and M. Boks, Beyond symptom dimensions: Schizophrenia risk factors for patient groups derived by latent class analysis, Schizophr. Res. 115 (2009), pp. 346-350.
    • (2009) Schizophr. Res , vol.115 , pp. 346-350
    • Leask, S.1    Vermunt, J.2    Done, D.3    Crow, T.4    Blows, M.5    Boks, M.6
  • 36
    • 84972808999 scopus 로고
    • Estimating normal means with a conjugate style Dirichlet process prior
    • S.N. MacEachern, Estimating normal means with a conjugate style Dirichlet process prior, Comm. Stat. Simul. Comput. 23 (1994), pp. 727-741.
    • (1994) Comm. Stat. Simul. Comput , vol.23 , pp. 727-741
    • Maceachern, S.N.1
  • 37
    • 0032221058 scopus 로고    scopus 로고
    • Estimating mixture of Dirichlet process models
    • S.N. MacEachern and P. Müller, Estimating mixture of Dirichlet process models, J. Comput. Graph. Stat. 7 (1998), pp. 223-238.
    • (1998) J. Comput. Graph. Stat , vol.7 , pp. 223-238
    • Maceachern, S.N.1    Müller, P.2
  • 38
    • 33750274518 scopus 로고    scopus 로고
    • Bayesian modelling and inference on mixtures of distributions
    • J.M. Marin, K.L. Mengersen, and C.P. Robert, Bayesian modelling and inference on mixtures of distributions, Handbook of Stat. 25 (2005), pp. 459-507.
    • (2005) Handbook of Stat , vol.25 , pp. 459-507
    • Marin, J.M.1    Mengersen, K.L.2    Robert, C.P.3
  • 40
    • 0036739286 scopus 로고    scopus 로고
    • Bayesian infinite mixture model based clustering of gene expression profiles
    • M. Medvedovic and S. Sivaganesan, Bayesian infinite mixture model based clustering of gene expression profiles, Bioinformatics 18 (2002), pp. 1194-1206.
    • (2002) Bioinformatics , vol.18 , pp. 1194-1206
    • Medvedovic, M.1    Sivaganesan, S.2
  • 41
    • 77950032550 scopus 로고    scopus 로고
    • Markov Chain sampling methods for Dirichlet process mixture models
    • R.M. Neal, Markov Chain sampling methods for Dirichlet process mixture models, J. Comput. Graph. Stat. 9 (2000), pp. 249-265.
    • (2000) J. Comput. Graph. Stat , vol.9 , pp. 249-265
    • Neal, R.M.1
  • 42
    • 1642370803 scopus 로고    scopus 로고
    • Slice sampling
    • R.M. Neal, Slice sampling, Ann. Stat. 31 (2003), pp. 705-741.
    • (2003) Ann. Stat , vol.31 , pp. 705-741
    • Neal, R.M.1
  • 43
    • 1842431459 scopus 로고    scopus 로고
    • Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities
    • D.R. Nyholt, N.G. Gillespie, A.C. Heath, K.R. Merikangas, D.L. Duffy, and N.G. Martin, Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities, Genet. Epidemiol. 26 (2004), pp. 231-244.
    • (2004) Genet. Epidemiol , vol.26 , pp. 231-244
    • Nyholt, D.R.1    Gillespie, N.G.2    Heath, A.C.3    Merikangas, K.R.4    Duffy, D.L.5    Martin, N.G.6
  • 44
    • 0042591659 scopus 로고    scopus 로고
    • The Unified Parkinson's Disease Rating Scale (UPDRS): Status and recommendations
    • Movement Disorder Society Task Force on Rating Scales for Parkinson's Disease
    • Movement Disorder Society Task Force on Rating Scales for Parkinson's Disease, The Unified Parkinson's Disease Rating Scale (UPDRS): Status and recommendations, Mov. Disord. 18 (2003), pp. 738-750.
    • (2003) Mov. Disord , vol.18 , pp. 738-750
  • 47
    • 77953530161 scopus 로고    scopus 로고
    • The identification of Parkinson's disease subtypes using cluster analysis: A systematic review
    • S.M. van Rooden, W.J. Heiser, J.N. Kok, D. Verbaan, J.J van Hilten, and J. Marinus, The identification of Parkinson's disease subtypes using cluster analysis: A systematic review, Mov. Disord. 25 (2010), pp. 969-978.
    • (2010) Mov. Disord , vol.25 , pp. 969-978
    • van Rooden, S.M.1    Heiser, W.J.2    Kok, J.N.3    Verbaan, D.4    van Hilten, J.J.5    Marinus, J.6
  • 49
    • 0034005254 scopus 로고    scopus 로고
    • Parkinson's disease subtypes: Clinical classification and ventricular cerebrospinal fluid analysis
    • M.C. Schiess, H. Zheng, V.M. Soukup, J.G. Bonnen, and H.J. Nauta, Parkinson's disease subtypes: Clinical classification and ventricular cerebrospinal fluid analysis, Parkinsonism Relat. Disord. 6 (2000), pp. 69-76.
    • (2000) Parkinsonism Relat. Disord , vol.6 , pp. 69-76
    • Schiess, M.C.1    Zheng, H.2    Soukup, V.M.3    Bonnen, J.G.4    Nauta, H.J.5
  • 50
    • 0000720609 scopus 로고
    • A constructive definition of Dirichlet priors
    • J. Sethuraman, A constructive definition of Dirichlet priors, Statist. Sinica 4 (1994), pp. 639-650.
    • (1994) Statist. Sinica , vol.4 , pp. 639-650
    • Sethuraman, J.1
  • 51
    • 47049121610 scopus 로고    scopus 로고
    • Distinguishing phenotypes of childhood wheeze and cough using latent class analysis
    • B. Spycher, M. Silverman, A. Brooke, C. Minder, and C. Kuehni, Distinguishing phenotypes of childhood wheeze and cough using latent class analysis, Eur. Respir. J. 31 (2008), pp. 974-981.
    • (2008) Eur. Respir. J , vol.31 , pp. 974-981
    • Spycher, B.1    Silverman, M.2    Brooke, A.3    Minder, C.4    Kuehni, C.5
  • 52
    • 0034354410 scopus 로고    scopus 로고
    • Dealing with label switching in mixture models
    • M. Stephens, Dealing with label switching in mixture models, J. R. Statist. Soc. Ser. B 62 (2000), pp. 795-809.
    • (2000) J. R. Statist. Soc. Ser. B , vol.62 , pp. 795-809
    • Stephens, M.1
  • 54
    • 0029937494 scopus 로고    scopus 로고
    • Epidemiology of Parkinson's disease
    • C.M. Tanner and S.M. Goldman, Epidemiology of Parkinson's disease, Neurol. Clin. 14 (1996), pp. 317-335.
    • (1996) Neurol. Clin , vol.14 , pp. 317-335
    • Tanner, C.M.1    Goldman, S.M.2
  • 55
    • 82455205691 scopus 로고    scopus 로고
    • An enriched conjugate prior for Bayesian nonparametric inference
    • S. Wade, S. Mongelluzzo, and S. Petrone, An enriched conjugate prior for Bayesian nonparametric inference, Bayesian Anal. 6 (2011), pp. 359-386.
    • (2011) Bayesian Anal , vol.6 , pp. 359-386
    • Wade, S.1    Mongelluzzo, S.2    Petrone, S.3
  • 56
    • 33847707418 scopus 로고    scopus 로고
    • Sampling the Dirichlet mixture model with slices
    • S.G. Walker, Sampling the Dirichlet mixture model with slices, Comm. Stat. Simul. Comput. 36 (2007), pp. 45-54.
    • (2007) Comm. Stat. Simul. Comput , vol.36 , pp. 45-54
    • Walker, S.G.1
  • 57
    • 84868152683 scopus 로고    scopus 로고
    • Latent class analysis identification of syndromes in Alzheimer's disease: A Bayesian approach
    • C.D. Walsh, Latent class analysis identification of syndromes in Alzheimer's disease: A Bayesian approach, Metodoloski Zvezki: Adv. Methodol. Stat. 3 (2006), pp. 147-162.
    • (2006) Metodoloski Zvezki: Adv. Methodol. Stat , vol.3 , pp. 147-162
    • Walsh, C.D.1
  • 59
    • 0002612391 scopus 로고
    • Hierarchical priors and mixture models, with application in regression and density estimation
    • A.F.M. Smith and P. Freeman, eds.,Wiley, Chichester
    • M. West, P. Müller, and M.D. Escobar, Hierarchical priors and mixture models, with application in regression and density estimation, in Aspects of Uncertainty: A Tribute to D.V. Lindley, A.F.M. Smith and P. Freeman, eds.,Wiley, Chichester, 1994, pp. 363-386.
    • (1994) Aspects of Uncertainty: A Tribute to D.V. Lindley , pp. 363-386
    • West, M.1    Müller, P.2    Escobar, M.D.3
  • 61
    • 0000039525 scopus 로고
    • A kth nearest neighbour clustering procedure
    • M.A. Wong and T. Lane, A kth nearest neighbour clustering procedure, J. R. Statist. Soc. Ser. B 45 (1983), pp. 362-368.
    • (1983) J. R. Statist. Soc. Ser. B , vol.45 , pp. 362-368
    • Wong, M.A.1    Lane, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.