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Volumn 8, Issue 3, 2014, Pages 1281-1313

Joint modeling of multiple time series via the beta process with application to motion capture segmentation

Author keywords

Bayesian nonparametrics; Beta process; Hidden Markov models; Motion capture; Multiple time series

Indexed keywords


EID: 84908309028     PISSN: 19326157     EISSN: 19417330     Source Type: Journal    
DOI: 10.1214/14-AOAS742     Document Type: Article
Times cited : (103)

References (50)
  • 1
    • 0034954376 scopus 로고    scopus 로고
    • Aligning gene expression time series with time warping algo- rithms
    • AACH, J. and CHURCH, G. (2001). Aligning gene expression time series with time warping algo- rithms. Bioinformatics 17 495-508.
    • (2001) Bioinformatics , vol.17 , pp. 495-508
    • Aach, J.1    Church, G.2
  • 3
    • 33947231297 scopus 로고    scopus 로고
    • Mixed hidden Markov models: An extension of the hidden Markov model to the longitudinal data setting
    • MR2345538
    • ALTMAN, R. M. (2007). Mixed hidden Markov models: An extension of the hidden Markov model to the longitudinal data setting. J. Amer. Statist. Assoc. 102 201-210. MR2345538
    • (2007) J. Amer. Statist. Assoc , vol.102 , pp. 201-210
    • Altman, R.M.1
  • 4
    • 0001924713 scopus 로고
    • State space modeling of multiple time series
    • MR1108250
    • AOKI, M. and HAVENNER, A. (1991). State space modeling of multiple time series. Econometric Rev. 10 1-99. MR1108250
    • (1991) Econometric Rev , vol.10 , pp. 1-99
    • Aoki, M.1    Havenner, A.2
  • 10
    • 66249125931 scopus 로고    scopus 로고
    • Nonparametric Bayes local partition models for random effects
    • MR2507141
    • DUNSON, D. B. (2009). Nonparametric Bayes local partition models for random effects. Biometrika 96249-262. MR2507141
    • (2009) Biometrika , pp. 96249-96262
    • Dunson, D.B.1
  • 11
    • 78349297511 scopus 로고    scopus 로고
    • Multivariate kernel partition process mixtures
    • MR2777330
    • DUNSON, D. B. (2010). Multivariate kernel partition process mixtures. Statist. Sinica 20 1395-1422. MR2777330
    • (2010) Statist. Sinica , vol.20 , pp. 1395-1422
    • Dunson, D.B.1
  • 13
    • 85032752250 scopus 로고    scopus 로고
    • Bayesian nonpara- metric methods for learning Markov switching processes
    • FOX, E. B., SUDDERTH, E. B., JORDAN, M. I. and WILLSKY, A. S. (2010). Bayesian nonpara- metric methods for learning Markov switching processes. IEEE Signal Process. Mag. 27 43-54.
    • (2010) IEEE Signal Process. Mag , vol.27 , pp. 43-54
    • Fox, E.B.1    Sudderth, E.B.2    Jordan, M.I.3    Willsky, A.S.4
  • 14
    • 79952690893 scopus 로고    scopus 로고
    • Bayesian nonpara- metric inference of switching dynamic linear models
    • FOX, E. B., SUDDERTH, E. B., JORDAN, M. I. and WILLSKY, A. S. (2011a). Bayesian nonpara- metric inference of switching dynamic linear models. IEEE Trans. Signal Process. 59 1569-1585.
    • (2011) IEEE Trans. Signal Process , vol.59 , pp. 1569-1585
    • Fox, E.B.1    Sudderth, E.B.2    Jordan, M.I.3    Willsky, A.S.4
  • 15
    • 79952660404 scopus 로고    scopus 로고
    • A sticky HDP-HMM with application to speaker diarization
    • MR2840185
    • FOX, E. B., SUDDERTH, E. B., JORDAN, M. I. and WILLSKY, A. S. (2011b). A sticky HDP-HMM with application to speaker diarization. Ann. Appl. Stat. 5 1020-1056. MR2840185
    • (2011) Ann. Appl. Stat , vol.5 , pp. 1020-1056
    • Fox, E.B.1    Sudderth, E.B.2    Jordan, M.I.3    Willsky, A.S.4
  • 17
    • 0000207240 scopus 로고
    • Convergence rates of the Gibbs sampler, the Metropolis algorithm and other single-site updating dynamics
    • MR1210432
    • FRIGESSI, A., DI STEFANO, P., HWANG, C.-R. and SHEU, S. J. (1993). Convergence rates of the Gibbs sampler, the Metropolis algorithm and other single-site updating dynamics. J. Roy. Statist. Soc. Ser. B 55 205-219. MR1210432
    • (1993) J. Roy. Statist. Soc. Ser. B , vol.55 , pp. 205-219
    • Frigessi, A.1    Di Stefano, P.2    Hwang, C.-R.3    Sheu, S.J.4
  • 19
  • 20
    • 77956889087 scopus 로고
    • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    • MR1380810
    • GREEN, P. J. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82 711-732. MR1380810
    • (1995) Biometrika , vol.82 , pp. 711-732
    • Green, P.J.1
  • 21
    • 33645509944 scopus 로고    scopus 로고
    • Order-based dependent Dirichlet processes
    • MR2268037
    • GRIFFIN, J. E. and STEEL, M. F. J. (2006). Order-based dependent Dirichlet processes. J. Amer. Statist. Assoc. 101 179-194. MR2268037
    • (2006) J. Amer. Statist. Assoc , vol.101 , pp. 179-194
    • Griffin, J.E.1    Steel, M.F.J.2
  • 22
    • 0001241617 scopus 로고
    • Nonparametric Bayes estimators based on beta processes in models for life history data
    • MR1062708
    • HJORT, N. L. (1990). Nonparametric Bayes estimators based on beta processes in models for life history data. Ann. Statist. 18 1259-1294. MR1062708
    • (1990) Ann. Statist , vol.18 , pp. 1259-1294
    • Hjort, N.L.1
  • 24
    • 84877737377 scopus 로고    scopus 로고
    • Effective split merge Monte Carlo meth- ods for nonparametric models of sequential data
    • Lake Tahoe, NV, USA
    • HUGHES, M., FOX, E. B. and SUDDERTH, E. B. (2012). Effective split merge Monte Carlo meth- ods for nonparametric models of sequential data. In Advances in Neural Information Processing Systems (NIPS) 25. Lake Tahoe, NV, USA.
    • (2012) Advances in Neural Information Processing Systems (NIPS) , pp. 25
    • Hughes, M.1    Fox, E.B.2    Sudderth, E.B.3
  • 25
    • 1842486852 scopus 로고    scopus 로고
    • A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model
    • MR2044876
    • JAIN, S. and NEAL, R. M. (2004). A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model. J. Comput. Graph. Statist. 13 158-182. MR2044876
    • (2004) J. Comput. Graph. Statist , 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
    • MR2342168
    • JAIN, S. and NEAL, R. M. (2007). Splitting and merging components of a nonconjugate Dirichlet process mixture model. Bayesian Anal. 2 445-472. MR2342168
    • (2007) Bayesian Anal , vol.2 , pp. 445-472
    • Jain, S.1    Neal, R.M.2
  • 27
    • 84969653882 scopus 로고
    • Completely random measures. Pacific
    • MR0210185
    • KINGMAN, J. F. C. (1967). Completely random measures. Pacific J. Math. 21 59-78. MR0210185
    • (1967) J. Math , vol.21 , pp. 59-78
    • Kingman, J.F.C.1
  • 28
    • 0003523893 scopus 로고
    • Oxford Univ. Press, New York. MR1207584
    • KINGMAN, J. F. C. (1993). Poisson Processes. Oxford Univ. Press, New York. MR1207584
    • (1993) Poisson Processes
    • Kingman, J.F.C.1
  • 29
    • 65949103420 scopus 로고    scopus 로고
    • Segmenting bacterial and viral DNA sequence align- ments with a trans-dimensional phylogenetic factorial hidden Markov model
    • MR2750008
    • LEHRACH, W. P. and HUSMEIER, D. (2009). Segmenting bacterial and viral DNA sequence align- ments with a trans-dimensional phylogenetic factorial hidden Markov model. J. R. Stat. Soc. Ser. C. Appl. Stat. 58 307-327. MR2750008
    • (2009) J. R. Stat. Soc. Ser. C. Appl. Stat , vol.58 , pp. 307-327
    • Lehrach, W.P.1    Husmeier, D.2
  • 31
    • 0008766414 scopus 로고    scopus 로고
    • Peskun’s theorem and a modified discrete-state Gibbs sampler
    • MR1423883
    • LIU, J. S. (1996). Peskun’s theorem and a modified discrete-state Gibbs sampler. Biometrika 83 681-682. MR1423883
    • (1996) Biometrika , vol.83 , pp. 681-682
    • Liu, J.S.1
  • 39
    • 36248955396 scopus 로고    scopus 로고
    • Music analysis using hidden Markov mixture models
    • MR2469377
    • QI, Y., PAISLEY, J. W. and CARIN, L. (2007). Music analysis using hidden Markov mixture models. IEEE Trans. Signal Process. 55 5209-5224. MR2469377
    • (2007) IEEE Trans. Signal Process , vol.55 , pp. 5209-5224
    • Qi, Y.1    Paisley, J.W.2    Carin, L.3
  • 40
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • RABINER, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77 257-286.
    • (1989) Proceedings of the IEEE , vol.77 , pp. 257-286
    • Rabiner, L.R.1
  • 45
    • 0000576595 scopus 로고
    • Markov chains for exploring posterior distributions
    • MR1329166
    • TIERNEY, L. (1994). Markov chains for exploring posterior distributions. Ann. Statist. 22 1701-1762. MR1329166
    • (1994) Ann. Statist , vol.22 , pp. 1701-1762
    • Tierney, L.1
  • 46
    • 0036566199 scopus 로고    scopus 로고
    • Image segmentation by data-driven Markov chain Monte Carlo
    • TU, Z. and ZHU, S. C. (2002). Image segmentation by data-driven Markov chain Monte Carlo. IEEE Trans. Pattern Anal. Mach. Intell. 24 657-673.
    • (2002) IEEE Trans. Pattern Anal. Mach. Intell , vol.24 , pp. 657-673
    • Tu, Z.1    Zhu, S.C.2


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