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Publications of Mike West    :chronological  combined  bibtex listing:

Books

  1. Bayesian Statistics 9, edited by J.M. Bernardo, M.J., Bayarri, J.O. Berger, A.P. David, D. Heckerman, A.F.M. Smith and M. West (2011), Oxford University Press (in press.)
  2. The Handbook of Applied Bayesian Analysis, edited by A. O'Hagan and M. West (2010), Oxford University Press, ISBN 978-0-19-954890-3 [html]
  3. Raquel Prado and Mike West, Time Series: Modelling, Computation and Inference (2010), Chapman & Hall/CRC Press, The Taylor Francis Group, ISBN 978-1-420093360 [available here]
  4. Bayesian Statistics 8, edited by J.M. Bernardo, M.J., Bayarri, J.O. Berger, A.P. David, D. Heckerman, A.F.M. Smith and M. West (2007), Oxford University Press [available here]
  5. Bayesian Statistics 7, edited by J.M. Bernardo, M.J., Bayarri, J.O. Berger, A.P. David, D. Heckerman, A.F.M. Smith and M. West (2003), Oxford University Press [available here]
  6. Case Studies in Bayesian Statistics V, edited by C. Gatsonis et al (2001), Springer-Verlag, New York
  7. Case Studies in Bayesian Statistics IV, edited by C. Gatsonis et al. (1998), Springer-Verlag, New York
  8. M. West and P.J. Harrison, Bayesian Forecasting and Dynamic Models (1997), Springer-Verlag, New York (2nd Edn. - 1989 1st Edn..) [html]
  9. A. Pole, M. West, and P.J. Harrison, Applied Bayesian Forecasting and Time Series Analysis (1994), Chapman-Hall, New York [html]

Papers Published

  1. F. Bonassi, L.You and M. West, Bayesian learning from marginal data in bionetwork models, Department of Statistical Science, Duke University: Discussion Paper, vol. 11-07 (2011) [html]
  2. A. Cron and M. West, Efficient classification-based relabeling in mixture models, The American Statistican, vol. 65 (2011), pp. 16-20 [html], [doi]
  3. Q. Wang and M. West, Model-controlled flooding with applications to image preprocessing and segmentation, Department of Statistical Science, Discussion Paper 11-05 (2011) [html]
  4. I. Manolopoulou, M.P. Matheu, M.D. Cahalan, M. West and T.Kepler, Bayesian spatio-dynamic modelling in cell motility studies: Learning nonlinear taxic fields guiding immune response, Discussion Paper 11-01, Department of Statistical Science (2011) [html]
  5. L. Lin, C. Chan and M. West, Discriminative information analysis in mixture modelling, Working Paper, Department of Statistical Science, Duke University no. 10-23 (2010) (Submitted for publication.) [html]
  6. C. Mukherjee and P. S. Kasibhatla and M. West, Bayesian statistical modeling of spatially correlated structure in atmospheric tracer inverse analysis, Working Paper, Department of Statistical Science, Duke University no. 10-24 (2010) (Submitted for publication.)
  7. C. Mukherjee and P. S. Kasibhatla and M. West, Spatially-varying models and inference for high-resolution lattice data, Working Paper, Department of Statistical Science, Duke University (2010)
  8. J. Nakajima and M. West, Bayesian analysis of latent threshold dynamic models, Working Paper, Department of Statistical Science, Duke University no. 10-25 (2010) (Submitted for publication.)
  9. D. Merl, J.E. Lucas, J.R. Nevins, H. Shen and M. West, Trans-study projection of genomic biomarkers using sparse factor regression models, in The Handbook of Applied Bayesian Analysis, edited by A. O’Hagan and M. West (2010), Oxford University Press, ISBN 978-0-19-954890-3 [html]
  10. J.E. Lucas, C.M. Carvalho, D. Merl and M. West, In-vitro to In-vivo factor profiling in expression genomics, in Bayesian Modelling in Bioinformatics, edited by D. Dey, S. Ghosh and B. Mallick (2010), pp. 293-316, Chapman & Hall/CRC Press [html]
  11. Q. Wang, J. Niemi, C.M. Tan, L. You & M. West, Image segmentation and dynamic lineage analysis in single-cell fluorescent microscopy, Cytometry A, vol. 77 no. 101-110 (2010) (First published Oct 20 2009, doi:10.1002/cyto.a.20812.) [html]
  12. H. Shen and M. West, Bayesian modelling for biological pathway annotation of gene expression pathway signatures, in Frontiers of Statistical Decision Making and Bayesian Analysis, edited by M-H. Chen, D.K. Dey, P. Mueller, D. Sun and K. Ye (2010), pp. 285-302, New York: Springer-Verlag [html]
  13. J. Niemi & M. West, Adaptive mixture modelling Metropolis methods for Bayesian analysis of non-linear state-space models, Journal of Computational and Graphical Statistics, vol. 19 (2010), pp. 260-280 (doi:10.1198/jcgs.2010.08117.) [html]
  14. M. West, Bayesian Forecasting, in Methods and Applications of Statistics in Business, Finance and Management Science, edited by N. Balakrishnan (2010), Wiley, Hoboken NJ, ISBN 978-0-470-40510-9
  15. R. Yoshida and M. West, Bayesian learning in sparse graphical factor models via annealed entropy, Journal of Machine Learning Research, vol. 11 (2010), pp. 1771-1798 [html]
  16. C. Chan, L. Lin, J. Frelinger, V. Hebert, D. Gagnon, C. Landry, R. P. Sekaly, J. Enzor, J. Staats, K. J. Weinhold, M. Jaimes, and M. West, Optimization of a highly standardized carboxyfluorescein succinimidyl ester flow cytometry panel and gating strategy design with discriminative information measure evaluation, Cytometry A, vol. 77 (2010), pp. 1126–1136 [html]
  17. C. Ji, H. Shen and M. West, Bounded approximations for marginal likelihoods, Submitted (2010) [html]
  18. J.L. Chen, D. Merl, C.W. Peterson, J. WU, P.Y. Liu, H. Yin, D.M. Muoio, D.E. Ayers, M. West and J.T.A. Chi, Lactic acidosis triggers starvation response with paradoxical induction of TXNIP through MondoA, PLoS Genetics, vol. 6 (2010), pp. e1001093 [html], [doi]
  19. G. Yao, C. Tan, M. West, J.R. Nevins and L. You, A minimal gene circuit underlying the bistable cell cycle entry, Submitted (2010) [html]
  20. I. Manolopolou, X. Wang, C. Ji, H.E. Lynch, S. Stewart, G.D. Sempowski, S.M. Alam, M. West and T.B. Kepler, Statistical analysis of immunofluorescent histology, Submitted (2010) [html]
  21. I. Manolopolou, C. Chan and M. West, Selection sampling from large data sets for targeted inference in mixture modeling (with discussion), Bayesian Analysis, vol. 5 (2010), pp. 429-450 [html], [doi]
  22. M. Suchard, Q. Wang, C. Chan, J. Frelinger, A. Cron and M. West, Understanding GPU programming for statistical computation: Studies in massively parallel massive mixtures, Journal of Computational and Graphical Statistics, vol. 19 (2010), pp. 419-438 [html], [doi]
  23. C. Mukherjee and M. West, Sequential Monte Carlo in model comparison: Example in cellular dynamics in systems biology, JSM Proceedings,Section on Bayesian Statistical Science. Alexandria, VA: American Statistical Association (2009), pp. 1274-1287 [html]
  24. J.E. Lucas, C.M. Carvalho and M. West, A Bayesian analysis strategy for cross-study translation of gene expression biomarkers, Statistical Applications in Genetics and Molecular Biology, vol. 8 no. 1 (2009), pp. Article 11 [html]
  25. J.E. Lucas, C.M. Carvalho, J-T.A. Chi and M. West, Cross-study projections of genomic biomarkers: An evaluation in cancer genomics, PLoS One, vol. 4 no. 2 (2009), pp. e4523 [html]
  26. J. Chang, C. Carvalho, S. Mori, A. Bild, Q. Wang, M. West and J.R. Nevins, A genomic strategy to elucidate modules of oncogenic pathway signaling networks, Molecular Cell, vol. 34 no. 1 (2009), pp. 104-114 ( This paper was selected for invited commentary in Molecular Cell, and research highlight in Nature Genetics, April 2009. This paper was also selected and discussed as one of the “2009: Signaling Breakthroughs of the Year” papers in Science Signaling, January 2010..) [html]
  27. F. Liang, K. Mao, M. Liao, S. Mukherjee and M. West, Non-parametric Bayesian kernel models, Department of Statistical Science, Discussion Paper 07-10 (2009) (Submitted for publication.) [html]
  28. H. Wang and M. West, Bayesian analysis of matrix normal graphical models, Biometrika, vol. 96 (2009), pp. 821-834 [html], [doi]
  29. C. Ji, D. Merl, T.B. Kepler and M. West, Spatial mixture modelling for unobserved point processes: Application to immunofluorescence histology, Bayesian Analysis, vol. 4 (2009), pp. 297-316 [html]
  30. D. Merl, J. Lin-Yu Chen, J.T. Chi and M. West, Integrative analysis of cancer gene expression studies using Bayesian latent factor modelling, Annals of Applied Statistics, vol. 3 (2009), pp. 1675-1694 (First published online, September 2009.) [html], [doi]
  31. F. Liu and M. West, A dynamic modelling strategy for Bayesian computer model emulation, Bayesian Analysis, vol. 4 (2009), pp. 393-412 [html]
  32. C.M. Carvalho, J.E. Lucas, Q. Wang, J. Chang, J.R. Nevins and M. West, High-dimensional sparse factor modelling - Applications in gene expression genomics, Journal of the American Statistical Association, vol. 103 (2008), pp. 1438–1456 [html]
  33. J.L. Chen, J.E. Lucas, T. Schroeder, S. Mori, J. Wu, J.R. Nevins, M. Dewhirst, M. West & J-T.A. Chi, Genomic analysis of response to lactic acidosis and acidosis in human cancers, PLoS Genetics, vol. 4 no. 12 (2008), pp. e1000293 [html]
  34. C. Chan, F. Feng, M. West and T. Kepler, Statistical mixture modelling for cell subtype identification in flow cytometry, Cytometry, A, vol. 73 no. 693-701 (2008) [html]
  35. P.J. Goldschmidt-Clermont, C. Dong, M. West and D.M. Seo and, Of cardiovascular illness and diversity of biological response, Trends in Cardiovascular Medicine, vol. 18 no. 5 (2008), pp. 194-197 [issues]
  36. Q. Wang, L. You & M. West, CellTracer: Software for automated image segmentation and lineage mapping for single-cell studies, Discussion Paper 08-22, Department of Statistical Science, Duke University (2008) [html]
  37. M. Xu, M.C.J. Kao, J.Nunez-Iglesias, J.R. Nevins, M. West and X.J. Zhou, Characterizing disease-specific pathways and their coordination by integrative microarray analysis with application to cancer, BMC Genomics, vol. 9 no. Suppl 1:S12. (2008) [pdf]
  38. C.M. Carvalho and M. West, Dynamic matrix-variate graphical models, Bayesian Analysis, vol. 2 (2007), pp. 69-98 [pdf]
  39. C.M. Carvalho and M. West., Dynamic matrix-variate graphical models - A synopsis, edited by (eds: J.M. Bernardo, M.J. Bayarri, J.O. Berger, A.P. Dawid, D. Heckerman, A.F.M. Smith and M. West,, Bayesian Statistics, vol. 8 (2007), pp. 585-590, Oxford University Press [pdf]
  40. Y. Wu, H. Tjelmeland and M. West, Bayesian CART: Prior structure and MCMC computations, Journal of Computational and Graphical Statistics, vol. 16 no. 1 (2007), pp. 44-66 [html]
  41. C.Hans, A. Dobra and M. West, Shotgun stochastic search in regression with many predictors, Journal of the American Statistical Association, vol. 102 (2007), pp. 507-516 [html]
  42. F. Liang, S. Mukherjee and M. West, Understanding the use of unlabelled data in predictive modelling, Statistical Science, vol. 22 (2007), pp. 189-205 [45]
  43. C. Carvalho, H. Massam and M. West, Simulation of hyper-inverse Wishart distributions in graphical models, Biometrika, vol. 94 (2007), pp. 647-659 [html]
  44. Q. Wang, C. Carvalho, J.E. Lucas and M. West, BFRM: Bayesian factor regression modelling, Bulletin of the International Society for Bayesian Analysis, vol. 14 (2007), pp. 4-5 [pdf]
  45. H.K. Dressman, A. Berchuck, G. Chan, J. Zhai, A. Bild, R. Sayer, J. Cragun, J.P. Clarke, R. Whitaker, L.H. Li, J. Gray, J. Marks, G.S. Ginsburg, A. Potti, M. West, J.R. Nevins and J.M. Lancaster, An integrated genomic-based approach to personalized treatment of patients with advanced-stage ovarian cancer, Journal of Clinical Oncology, vol. 25 (2007), pp. 517-525
  46. C. Hans, Q. Wang, A. Dobra and M. West, SSS: High-dimensional Bayesian regression model search, Bulletin of the International Society for Bayesian Analysis, vol. 24 (2007), pp. 8-9 [pdf]
  47. David M. Seo, Pascal J. Goldschmidt-Clermont and Mike West, Of mice and men: Sparse statistical modelling in cardiovascular genomics, Annals of Applied Statistics, vol. 1 no. 1 (2007), pp. 152-178 [html]
  48. S.H. Cheng, C.F.Horng, M. West, E. Huang, J. Pittman, M.H. Tsou, H. Dressman, C.M. Chen, S.Y. Tsail, J.J. Jian, M.C. Liu, J.R. Nevins and A.T. Huang, Genomic prediction of loco-regional recurrence following mastectomy in breast cancer, Journal of Clinical Oncology, vol. 24 (2006), pp. 4594-4602 [pdf]
  49. A. Dobra, C. Tebaldi and M. West, Data augmentation in multi-way contingency tables with fixed marginal totals, Journal of Statistical Planning and Inference, vol. 136 (2006), pp. 355-372 [science]  [abs]
  50. A.H. Bild, G. Yao, J.T. Chang, Q. Wang, A. Potti, D. Chasse, M. Joshi, D. Harpole, J.M. Lancaster, A. Berchuck, J.A. Olson, J.R. Marks, H.K. Dressman, M.West and J.R. Nevins, Oncogenic pathway signatures in human cancers as a guide to targeted therapies, Nature, vol. 439 (2006), pp. 353-357 [html]
  51. M.A.R. Ferreira, M. West, H.Lee and D.Higdon, Multiscale and hidden resolution time series models, Bayesian Analysis, vol. 2 (2006), pp. 294-314 [pdf]
  52. C. Hans and M. West, High-dimensional regression in cancer genomics, Bulletin of the International Society for Bayesian Analysis, vol. 13 (2006), pp. 2-3 [pdf]
  53. H. Dressman, C. Hans, A. Bild, J. Olsen, E. Rosen, P.K. Marcom, V. Liotcheva, E. Jones, Z. Vujaskovic, J. Marks, M.W. Dewhirst, M. West, J.R. Nevins and K. Blackwell, Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant therapy, Clinical Cancer Research, vol. 12 (2006), pp. 819-216 [819]
  54. M. West, A.T. Huang, G.Ginsberg and J.R. Nevins, Embracing the complexity of genomic data for personalized medicine, Genome Research, vol. 16 (2006), pp. 559-566 [559]
  55. J. Lucas, C. Carvalho, Q. Wang, A. Bild, J.R. Nevins and M. West, Sparse statistical modelling in gene expression genomics, in Bayesian Inference for Gene Expression and Proteomics, edited by K.A. Do, P. Mueller and M. Vannucci (2006), pp. 155-176, Cambridge University Press [html]
  56. R. Karra, S. Wemullapalli, C. Dong, E.E. Herderick, X. Song, K. Slosek, J.R. Nevins, M. West, P.J. Goldschmidt-Clermont and D. Seo, Molecular evidence for arterial repair in atherosclerosis, Proceedings of the National Academy of Sciences, vol. 102 no. 46 (November, 2005), pp. 16789-16794 [16789]
  57. M. DeLong, G. Yao, Q. Wang, A. Dobra, E. Black, J. Chang, A. Bild, M.West, J. Nevins and H. Dressman, DIG - A system for gene annotation and functional discovery, Bioinformatics, vol. 21 (2005), pp. 2957 - 2959 [2957]
  58. P. Patil, M. West, H.W. Wheal, and D.A. Turner, Physiological and statistical approaches to modelling of synaptic responses, in Modeling in the Neurosciences: From Biological Systems to Neuromimetic Robots, 2nd Edn., edited by G.N. Reeke, R.R. Poznanski, K.A. Lindsay, J.R. Rosenberg and O. Sporns (2005), pp. 61-88, Taylor & Francis, CRC Press [html]
  59. E.P Black, T. Hallstrom, H.K. Dressman, M. West and J.R. Nevins, DIstinctions in the specificity of E2F function revealed by gene expression, Proceedings of the National Academy of Sciences, vol. 102 (2005), pp. 15948-53 [15948]
  60. M.A.R. Ferreira, D. Higdon, H.K. Lee and M. West, Multi-scale random field models, ISDS Discussion Paper #05-02 (2005) (Submitted for publication.) [html]
  61. A. Berchuck, E.S. Iversen, J.M. Lancaster, J. Pittman, J. Luo, P. Lee, S. Murphy, H.K. Dressman, P.G. Febbo, Mike West, J.R. Nevins and J.R. Marks, Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers, Clinical Cancer Research, vol. 11 (2005), pp. 3686-3696 [3686]
  62. B. Jones, A. Dobra, C. Carvalho, C. Hans, C. Carter and M. West, Experiments in stochastic computation for high-dimensional graphical models, Statistical Science, vol. 20 (2005), pp. 388-400 [html]
  63. Jeremy Rich, Beatrix Jones, Chris Hans, Ed Iversen, Roger McClendon, Ahmed Rasheed, Darell Bigner, Adrian Dobra, Holly Dressman, Joseph Nevins and Mike West, Gene expression profiling and genetic markers in glioblastoma survival, Cancer Research, vol. 65 (2005), pp. 4051-4058 [html]
  64. Beatrix Jones and Mike West, Covariance decomposition in undirected Gaussian graphical models, Biometrika, vol. 92 (2005), pp. 779-786 [779]
  65. S.J. Godsill, A. Doucet and M. West, Monte Carlo smoothing for non-linear time series, Journal of the American Statistical Association, vol. 99 (2004), pp. 156-168 [html]
  66. A. Berchuk, E.S. Iversen, J.M. Lancaster, H.K. Dressman, M. West, J.R. Nevins and J.R. Marks, Prediction of optimal versus suboptimal cytoreduction of advanced stage serious ovarian cancer using microarrays, Amer. J. Obstetrics & Gynecology, vol. 190 (2004), pp. 910-25
  67. E.P. Hoffman, T. Awad, A. Spira, J. Palma, T. Webster, G. Wright, J. Buckley, R. Davis, E. Hubbell, W. Jones, R. Tibshirani, R. Tompkins, T. Triche, W. Xiao, M. West and J.A. Warrington, Expression profiling: Best practices for Affymetrix array data generation and interpretation for clinical trials, Nature Reviews Genetics, vol. 5 (2004), pp. 229-237 [html]
  68. J. Pittman, E. Huang, Q. Wang, J. Nevins and M. West, Bayesian analysis of binary prediction tree models for retrospectively sampled outcomes, Biostatistics, vol. 5 (2004), pp. 587-601 [html]
  69. A. Dobra, B. Jones, C. Hans, J.R. Nevins and M. West, Sparse graphical models for exploring gene expression data, Journal of Multivariate Analysis, vol. 90 (2004), pp. 196-212 [html]
  70. J. Pittman, E. Huang, H. Dressman, C.F. Horng, S.H. Cheng, M.H. Tsou, C.M. Chen, A. Bild, E.S. Iversen, A.T. Huang, J.R. Nevins and M. West, Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes, Proceedings of the National Academy of Sciences, vol. 101 (2004), pp. 8431-8436 [html]
  71. D.M. Seo, T. Wang, H. Dressman, E.E. Herderick, E.S. Iversen, C. Dong, K. Vata, C.A. Milano, F. Rigat, J. Pittman, J.R. Nevins, M. West and P.J. Goldschmidt-Clermont, Gene expression phenotypes of atherosclerosis, Arteriosclerosis, Thrombosis and Vascular Biology, vol. 24 (2004), pp. 1922-1927 [1922]
  72. M. West, Bayesian factor regression models in the "large p, small n" paradigm, in Bayesian Statistics 7, edited by J.M. Bernardo et al. (2003), pp. 723-732, Oxford [html]
  73. E. Huang, M. West and J.R. Nevins, Gene expression phenotypes of oncogenic pathways, Cell Cycle, vol. 2 (2003), pp. 415-417 [abstract.php]
  74. E. Huang, S. Ishida, J. Pittman, H. Dressman, A. Bild, M. D'Amico, R. Pestell, M. West and J.R. Nevins, Gene expression phenotypic models that predict the activity of oncogenic pathways, Nature Genetics, vol. 34 (2003), pp. 226-230 [html]
  75. H. Lopes and M. West, Bayesian model assessment in factor analysis, Statistica Sinica, vol. 14 (2003), pp. 41-67 [html]
  76. J.R. Nevins, E.S. Huang, H. Dressman, J. Pittman, A.T. Huang and M. West, Towards integrated clinico-genomic models for personalized medicine: Combining gene expression signatures and clinical factors in breast cancer outcomes prediction, Human Molecular Genetics, vol. 12 (2003), pp. 153-157 [html]
  77. S. Paddock, F. Ruggeri, M. Lavine and M. West, Tree models for nonparametric Bayesian inference, Statistica Sinica, vol. 13 (2003), pp. 443-460 [html]
  78. J. Pittman, E. Huang, J.R. Nevins and M. West, Prediction tree models in clinico-genomics, Bulletin of the International Statistical Institute, vol. 54 (2003), pp. 76 [html]
  79. E. Huang, S. Chen, H. Dressman, J. Pittman, M.H. Tsou, C.F. Horng, A. Bild, E.S. Iversen, M. Liao, C.M. Chen, M. West, J.R. Nevins and A.T. Huang, Gene expression predictors of breast cancer outcomes, The Lancet, vol. 361 (2003), pp. 1590-1596 [html]
  80. E.P. Black, E. Huang, H. Dressman, S. Ishida, M. West and J.R. Nevins, Distinct gene expression phenotypes of cells lacking Rb and Rb family members, Cancer Research, vol. 63 (2003), pp. 3716-3723 [html]
  81. M.A.R. Ferreira, Z. Bi, M. West, H. Lee and D. Higdon, Multiscale modelling of 1-D permeability fields, in Bayesian Statistics 7, edited by J.O. Bernardo et al. (2003), OUP [html]
  82. C. Tebaldi, M. West, and A.F. Karr, Statistical analyses of freeway traffic flows, Journal of Forecasting, vol. 21 (2002), pp. 39-68 [html]
  83. H. Lee, D. Higdon, Z. Bi, M. Ferreira and M. West, Markov random field models for high-dimensional parameters in simulations of fluid flow in porous media, Technometrics, vol. 44 (2002), pp. 230-241 [html]
  84. E. Huang, M. West, and J.R. Nevins, Gene expression profiles and predicting clinical characteristics of breast cancer, Hormone Research, vol. 58 (2002), pp. 55-73 [55]
  85. W. Fong, S.J. Godsill, A. Doucet, and M. West, Monte Carlo smoothing with application to speech enhancement, IEEE Trans. Signal Processing, vol. 50 (2002), pp. 438-449 [html]
  86. J. Liu and M. West, Combined parameter and state estimation in simulation-based filtering, in Sequential Monte Carlo Methods in Practice, edited by A. Doucet, J.F.G. De Freitas, and N.J. Gordon (2001), pp. 197-217, New York: Springer-Verlag (ISBN 0-38795146-6.) [html]
  87. S.J. Godsill, A. Doucet and M. West, Maximum a posteriori sequence estimation using Monte Carlo particle filters, Annals of the Institute of Statistical Mathematics, vol. 53 (2001), pp. 82-96 [pdf]
  88. R. Prado, M. West, and A. Krystal, Multi-channel EEG analyses via dynamic regression models with time-varying lag/lead structure, Journal of the Royal Statistical Society (Ser. C - Applied Statistics), vol. 50 (2001), pp. 95-110 [html]
  89. M. West, C. Blanchette, H. Dressman, E. Huang, S. Ishida, R. Spang, H. Zuzan, J.R. Marks and J.R. Nevins, Predicting the clinical status of human breast cancer utilizing gene expression profiles, Proceedings of the National Academy of Sciences, vol. 98 (2001), pp. 11462-11467 [11462]
  90. R. Spang, H. Zuzan, M. West, J.R. Nevins, C. Blanchette and J.R. Marks, Prediction and uncertainty in the analysis of gene expression profiles, In Silico Biology, vol. 2 (2001), pp. 0033 [available here]
  91. S. Ishida, E. Huang, H. Zuzan, R. Spang, G. Leone, M. West, and J.R. Nevins, Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis, Molecular and Cellular Biology, vol. 21 (2001), pp. 4684-4699 [4684]
  92. R. Prado, G. Huerta and M. West, Bayesian time-varying autoregressions: Theory, methods and applications, Resenhas, vol. 4 (2001), pp. 405-422 [html]
  93. O. Aguilar and M. West, Bayesian dynamic factor models and portfolio allocation, Journal of Business and Economic Statistics, vol. 18 (2000), pp. 338-357 [html]
  94. A. Doucet, S.J. Godsill and M. West, Monte Carlo filtering and smoothing with application to time-varying spectral estimation, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. II (2000), pp. 701-704 (ISBN 0-7803-6296-9.) [pdf]
  95. J. Burgess, V. Lourdes and M. West, Profiling mental health provider trends in health care delivery systems, Health Services & Outcomes Research Methodology, vol. 100 (2000), pp. 253-276 [html]
  96. A.D. Krystal, M. West, R Prado, H.S. Greenside, S. Zoldi, and R.D. Weiner, The EEG Effects of ECT: Implications for rTMS, in Progress in Neuropsychopharmacology and Biological Psychiatry (1999) [html]
  97. G. Huerta and M. West, Bayesian inference on periodicities and component spectral structures in time series, Journal of Time Series Analysis, vol. 20 (1999), pp. 401-416 [html]
  98. M. West, R. Prado and A. Krystal, Evaluation and comparison of EEG traces: Latent structure in non-stationary time series, Journal of the American Statistical Association, vol. 94 (1999), pp. 1083-1095 [html]
  99. A.D. Krystal, R. Prado, and M. West, New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions, Clinical Neurophysiology, vol. 110 (1999), pp. 1-10 [html]
  100. G. Huerta, and M. West, Priors and component structurres in autoregressive time series, Journal of the Royal Statistical Society (Ser. B), vol. 61 (1999), pp. 881-899 [html]
  101. O. Aguilar, R. Prado, G. Huerta and M. West, Bayesian inference on latent structure in time series(with discussion), in Bayesian Statistics 6, edited by J.O. Bernardo et al. (1999), pp. 3-26, OUP [html]
  102. O. Aguilar and M. West, Analysis of hospital quality monitors using hierarchical time series models, in Case Studies in Bayesian Statistics, Vol. 4, edited by C. Gatsonis et al. (1999), Springer-Verlag, New York [html]
  103. A.D. Krystal, S. Zoldi, R. Prado, H.S. Greenside and M. West, The spatiotemporal dynamics of generalized tonic-clonic seizure EEG data: Relevance to the climinal practice of electroconvulsive therapy, in Nonlinear Dynamics and Brain Functioning, edited by N. Pradhan, P.E. Rapp and R. Sreenivasan (1999), New York: Novascience
  104. D.A. Turner, Y. Chen, H.V. Wheal and M. West, Statistical inference of synaptic responses: Physiological and statistical approaches, in Modelling in the Neurosciences: From Ion Channels to Neural Networks, edited by R.R. Poznanski (1999), pp. 39-78, London, Gordon & Breach Publishers
  105. C. Tebaldi and M. West, Bayesian inference on network traffic using link count data (with discussion), Journal of the American Statistical Association, vol. 93 (1998), pp. 557-576 [html]
  106. G. Huerta and M. West, Bayesian inference for unequally-spaced time series, Section on Bayesian Statistical Science, JSM Proceedings, ASA (1998), pp. 17-21
  107. S. Paddock, M. West, S. Young and M. Clyde, Mixture models in the exploration of structure-activity relationships in drug design, in Case Studies in Bayesian Statistics, Vol. 4, edited by C. Gatsonis et al. (1998), Springer-Verlag, New York [html]
  108. M.D. Escobar and M. West, Computing nonparametric hierarchical models, in Practical Non and Semiparametric Bayesian Statistics, edited by P. Müller et al. (1998), Springer-Verlag [html]
  109. M. West, Bayesian Forecasting, in Encyclopedia of Statistical Sciences, edited by S. Kotz, C.B. Read, and D.L. Banks (1998), Wiley
  110. G. Cao and M. West, Computing distributions of order statistics, Comunications in Statistics, vol. 26 (1997)
  111. C. Cargnoni, P. Müller and M. West, Bayesian forecasting of multinational time series through conditionally Gaussian dynamic models, Journal of the American Statistical Association, vol. 92 (1997), pp. 640-647
  112. P. Müller, M. West and S.N. MacEachern, Bayesian models for non-linear auto-regressions, Journal of Time Series Analysis, vol. 18 (1997), pp. 593-614 [html]
  113. M. West, Time series decomposition, Biometrika, vol. 84 (1997), pp. 489-494 [html]
  114. M. West, Hierarchical mixture models in neurological transmission analysis, Journal of the American Statistical Association, vol. 92 (1997), pp. 587-606
  115. D.A. Turner, Y. Chen, J. Isaac, M. West and H.V. Wheal, Heterogeneity between non-NMDA synaptic sites in paired-pulse plasticity of CA1 pyramidal neurons in the hippocampus, Journal of Physiology, vol. 500 (1997), pp. 441-461
  116. M. West, Modelling and robustness issues in Bayesian time series analysis (with discussion), in Bayesian Robustness, IMS Monographs, edited by J.O. Berger et al. (1997), pp. 231-252
  117. R. Prado and M. West, Exploratory modelling of multiple non-stationary time series: Latent process structure & decompositions, in Modelling Longitudinal and Spatially Correlated Data, edited by T. Gregoire (1997), Springer-Verlag
  118. G. Cao and M. West, Practical Bayesian inference using mixtures of mixtures, Biometrics, vol. 52 (1996), pp. 1334-1341
  119. P. Müller, A. Erkanli and M. West, Bayesian curve fitting using multivariate normal mixtures, Biometrika, vol. 83 (1996), pp. 67-79
  120. M. West, Inference in successive sampling discovery models, Journal of Econometrics, vol. 75 (1996), pp. 217-238 [html]
  121. M. West, Some statistical issues in Palaeoclimatology (with discussion), edited by J.O. Berger et al., Bayesian Statistics 5 (1996), OUP [html]
  122. M. West, Bayesian time series: Models and computations for the analysisd of time series in the physical sciences, in Maximum Entropy and Bayesian Methods 15, edited by K. Hanson and R. Silver (1996), Kluwer [html]
  123. M.D. Escobar and M. West, Bayesian density estimation and inference using mixtures, Journal of the American Statistical Association, vol. 90 (1995), pp. 577-588 [pdf]
  124. M. West, Bayesian inference in cyclical component dynamic linear models, Journal of the American Statistical Association, vol. 90 (1995), pp. 1301-1312
  125. M. West, Discovery sampling and selection models, in Statistical Decision Theory and Related Topics, edited by S.S. Gupta and J.O. Berger (1994), pp. 221-235, Springer-Verlag, New York [html]
  126. M. West and D.A. Turner, Deconvolution of mixtures in analysis of neural synaptic transmission, The Statistician, vol. 43 (1994), pp. 31-43
  127. M. West, P. Miller 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, edited by AFM Smith and PR Freeman (1994), pp. 363-386, London: Wiley [html]
  128. D.A. Turner and M. West, Statistical analysis of mixtures applied to postsynaptic potential fluctuations, Journal of Neuroscience Methods, vol. 47 (1993), pp. 1-23
  129. M. West, Approximating posterior distributions by mixtures, Journal of the Royal Statistical Society (Ser. B), vol. 54 (1993), pp. 553-568
  130. M. West, Mixture models, Monte Carlo, Bayesian updating and dynamic models, Computing Science and Statistics, vol. 24 (1993), pp. 325-333 [ps]
  131. M. West and G. Cao, Assessing mechanisms of neural synaptic activity, in Case Studies in Bayesian Statistics, Vol. 1, edited by C. Gatsonis et al. (1993), Springer-Verlag, New York
  132. M. Lavine and M. West, A Bayesian method for classification and discrimination, Canadian Journal of Statistics, vol. 20 (1992), pp. 451-461
  133. M. West, Modelling agent forecast distributions, Journal of the Royal Society (Ser. B), vol. 54 (1992), pp. 553-567
  134. M. West and J. Crosse, Modelling of probabilistic agent opinion, Journal of the Royal Statistical Society (Ser. B), vol. 54 (1992), pp. 285-299
  135. M. West, Modelling with mixtures (with discussion), in Bayesian Statistics 4, edited by J.O. Berger et al. (1992), OUP
  136. M. West, On Bayesian statistics in astronomical investigation: Source detection with low particle counts, in Statistical Challenges in Modern Astronomy, edited by E.D. Fiegelson and G.J. Babu (1992), Springer-Verlag
  137. M. West, Modelling time-varying hazards and movariate effects (with discussion), in Survival Analysis: State of the Art, edited by J.P. Klein and P.K. Goel (1992), Kluwer
  138. P.J. Harrison and M. West, Dynamic linear model diagnostics, Biometrika, vol. 78 (1991), pp. 797-808
  139. M. West, Kernel density estimation and marginalisation consistency, Biometrika, vol. 78 (1991), pp. 421-425
  140. M. West and R.L. Winkler, Database error trapping and prediction, Journal of the American Statistical Association, vol. 86 (1991), pp. 987-996
  141. A. Pole and M. West, Efficient Bayesian learning in non-linear dynamic models, Journal of Forecasting, vol. 9 (1990), pp. 119-136
  142. A. Pole and M. West, Reference analysis of the DLM, Journal of Time Series Analysis, vol. 10 (1989), pp. 131-147
  143. M. West and P.J. Harrison, Subjective intervention in formal models, Journal of Forecasting, vol. 8 (1989), pp. 33-53
  144. M. West, Modelling expert opinion (with discussion), in Bayesian Statistics 3, edited by J.M. Bernardo et al. (1988), OUP [pdf]
  145. J.M. Quintana and M. West, Time series analysis of compositional data, in Bayesian Statistics 3, edited by J.M. Bernardo et al. (1988), OUP
  146. A. Pole, M. West, and P.J. Harrison, Non-normal and non-linear dynamic Bayesian modelling, in Bayesian Analysis of Time Series and Dynamic Models, edited by J.C. Spall (1988), Marcel Dekker, NY
  147. D. Gamerman and M. West, A time series application of dynamic survival models in unemployment studies, The Statistician, vol. 36 (1987), pp. 269-274
  148. P.J. Harrison and M. West, Practical Bayesian forecasting, The Statistician, vol. 36 (1987), pp. 115-125
  149. M. West, P.J. Harrison, and A. Pole, BATS: Bayesian Analysis of Time Series, The Professional Statistician, vol. 6 (1987), pp. 43-46
  150. M. West, On scale mixtures of normal distributions, Biometrika, vol. 74 (1987), pp. 646-648
  151. J.M. Quintana and M. West, An analysis of international exchange rates using multivariate DLMs, The Statistician, vol. 36 (1987), pp. 275-281
  152. M. West and J. Mortera, Bayesian models and methods for binary time series, in Probability and Bayesian Statistics, edited by R. Viertl (1987), Elsevier, Amsterdam
  153. M. West, Discussion of: Influence functionals for time series, Annals of Statistics, vol. 14 (1986), pp. 838-840
  154. M. West, Bayesian model monitoring, Journal of the Royal Statistical Society (Ser. B), vol. 48 (1986), pp. 70-78
  155. M. West and P.J. Harrison, Monitoring and adaptation in Bayesian forecasting models, Journal of the American Statistical Association, vol. 81 (1986), pp. 741-750
  156. M. West, P. Harrison, and H.S. Migon, Dynamic generalised linear models and Bayesian forecasting (with discussion), Journal of the American Statistical Association, vol. 80 (1985), pp. 73-97
  157. M. West, Generalised linear models: scale parameters, outlier accommodation and prior distributions (with discussion), edited by J.M. Barnardo et al., Bayesian Statistics 2 (1985), pp. 531-558, North Holland, Amsterdam
  158. M. West, Outlier models and prior distributions in Bayesian linear regression, Journal of the Royal Statistical Society (Ser. B), vol. 46 (1984), pp. 431-439
  159. M. West, Bayesian aggregation, Journal of the Royal Statistical Society (Ser. A), vol. 147 (1984), pp. 600-607 [pdf]
  160. I. Trimble, M. West, M.S. Knapp, R. Pownall, and A.F.M. Smith, Detection of renal allograft rejection by computer, British Medical Journal, vol. 286 (1983), pp. 1695-1699
  161. A.F.M. Smith and M. West, Monitoring renal transplants: An application of the multi-process Kalman filter, Biometrics, vol. 39 (1983), pp. 867-878 [pdf]
  162. A.F.M. Smith, M. West, K. Gordon, M.S. Knapp, and I. Trimble, Monitoring kidney transplant patients, The Statistician, vol. 32 (1983), pp. 46-54
  163. M. West, Robust sequential approximate Bayesian estimation, Journal of the Royal Statistical Society (Ser. B), vol. 43 (1981), pp. 157-166