Scholars@Duke

• Recognition
• 

  In the News

  • MAY 27, 2021

    May Books: Mike West "Time Series: Modeling, Computation, and Inference"

  • NOV 7, 2018

    Statistical Science Professor Awarded for Contributions to Bayesian Analysis

  • OCT 13, 2014

    Mike West Honored by NC Chapter of American Statistical Association

  • SEP 25, 2014

    West Honored With Inaugural Award of International Bayesian Society

  • JUN 25, 2014

    Ruilin Zhong: Going Far With Interests in Economics and Statistics
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  Awards & Honors

  • Akaike Memorial Lecture Award. Institute of Statistical Mathematics (ISM) and Japan Statistical Society (JSS). September 2019
  • American Statistical Association, NC Chapter Award. American Statistical Association. 2014
  • Zellner Medal. Zellner Medal, International Society for Bayesian Analysis (ISBA). 2014
  • Inaugural Fellow. International Society for Bayesian Analysis. 2012
  • Mitchell Prize. International Society for Bayesian Analysis, & Bayesian Statistical Science Section of the American Statistical Association. 2012
  • Chair, Section on Bayesian Statistical Science. American Statistical Association. 2010
  • President. International Society for Bayesian Analysis. 2009
  • Best Papers of Annals of Applied Statistics 2007 Award. Annals of Applied Statistics. August 2008
  • Outstanding Statistical Application. American Statistical Association. 1999
  • Mitchell Prize. International Society for Bayesian Analysis, & Bayesian Statistical Science Section of the American Statistical Association. . 1997
  • Mitchell Prize. International Society for Bayesian Analysis, & Bayesian Statistical Science Section of the American Statistical Association. 1994
  • ASA Fellow. American Statistical Association. 1993
• Research
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  External Relationships

  • Amazon
• Publications & Artistic Works
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  Selected Publications

  • Books

    • Prado, Raquel, Marco A. R. Ferreira, and Mike West. Time Series: Modeling, Computation and Inference. Chapman and Hall/CRC Press, 2021.
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    • West, Mike, and Jeff Harrison. Bayesian Forecasting and Dynamic Models. Springer Science & Business Media, 2013.
    • O’ Hagan, Anthony, and Mike West, eds. The Oxford Handbook of Applied Bayesian Analysis, 2010.
    • Prado, R., and M. West. Time series: Modeling, computation, and inference, 2010. https://doi.org/10.1201/9781439882757.
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    • West, Mike, and Jeff Harrison. Bayesian Forecasting and Dynamic Models. Springer, 1999.
    • Pole, A., M. West, and P. J. Harrison. Applied Bayesian Forecasting & Time Series Analysis. Chapman-Hall, 1994.

  • Academic Articles

    • Yanchenko, Anna K., Di Daniel Deng, Jinglan Li, Andrew J. Cron, and Mike West. “Hierarchical Dynamic Modeling for Individualized Bayesian Forecasting,” January 9, 2021.
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    • Berry, L. R., and M. West. “Bayesian Forecasting of Many Count-Valued Time Series.” Journal of Business and Economic Statistics 38, no. 4 (October 1, 2020): 872–87. https://doi.org/10.1080/07350015.2019.1604372.
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    • McAlinn, K., K. A. Aastveit, J. Nakajima, and M. West. “Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting.” Journal of the American Statistical Association 115, no. 531 (July 2, 2020): 1092–1110. https://doi.org/10.1080/01621459.2019.1660171.
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    • Berry, L. R., P. Helman, and M. West. “Probabilistic forecasting of heterogeneous consumer transaction–sales time series.” International Journal of Forecasting 36, no. 2 (April 1, 2020): 552–69. https://doi.org/10.1016/j.ijforecast.2019.07.007.
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    • West, M. “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions.” Annals of the Institute of Statistical Mathematics 72, no. 1 (February 1, 2020). https://doi.org/10.1007/s10463-019-00741-3.
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    • West, M. “Reply to Discussion of “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions”.” Annals of the Institute of Statistical Mathematics 72, no. 1 (February 1, 2020): 41–44. https://doi.org/10.1007/s10463-019-00744-0.
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    • Chen, X., D. Banks, and M. West. “Bayesian dynamic modeling and monitoring of network flows.” Network Science 7, no. 3 (September 1, 2019): 292–318. https://doi.org/10.1017/nws.2019.10.
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    • Crawford, Lorin, Seth R. Flaxman, Daniel E. Runcie, and Mike West. “VARIABLE PRIORITIZATION IN NONLINEAR BLACK BOX METHODS: A GENETIC ASSOCIATION CASE STUDY¹.” The Annals of Applied Statistics 13, no. 2 (June 17, 2019): 958–89. https://doi.org/10.1214/18-aoas1222.
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    • McAlinn, K., and M. West. “Dynamic Bayesian predictive synthesis in time series forecasting.” Journal of Econometrics 210, no. 1 (May 1, 2019): 155–69. https://doi.org/10.1016/j.jeconom.2018.11.010.
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    • Irie, K., and M. West. “Bayesian emulation for multi-step optimization in decision problems.” Bayesian Analysis 14, no. 1 (January 1, 2019): 137–60. https://doi.org/10.1214/18-BA1105.
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    • Yao, Yuling, Aki Vehtari, Daniel Simpson, and Andrew Gelman. “Using Stacking to Average Bayesian Predictive Distributions (with Discussion).” Bayesian Analysis 13, no. 3 (September 1, 2018). https://doi.org/10.1214/17-ba1091.
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    • Chen, X., K. Irie, D. Banks, R. Haslinger, J. Thomas, and M. West. “Scalable Bayesian Modeling, Monitoring, and Analysis of Dynamic Network Flow Data.” Journal of the American Statistical Association 113, no. 522 (April 3, 2018): 519–33. https://doi.org/10.1080/01621459.2017.1345742.
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    • Nakajima, J., and M. West. “Dynamics & sparsity in latent threshold factor models: A study in multivariate EEG signal processing.” Brazilian Journal of Probability and Statistics 31, no. 4 (January 1, 2017): 701–31. https://doi.org/10.1214/17-BJPS364.
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    • West, M., and L. F. Gruber. “Bayesian forecasting and scalable multivariate volatility analysis using simultaneous graphical dynamic linear models.” Econometrics and Statistics, 2017. https://doi.org/10.1016/j.ecosta.2017.03.003.
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    • Zhao, Z. Y., M. Xie, and M. West. “Dynamic dependence networks: Financial time series forecasting and portfolio decisions.” Applied Stochastic Models in Business and Industry 32, no. 3 (May 1, 2016): 311–32. https://doi.org/10.1002/asmb.2161.
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    • Zhao, Z., M. Xie, and M. West. “Rejoinder to ‘Dynamic dependence networks: Financial time series forecasting and portfolio decisions’.” Applied Stochastic Models in Business and Industry 32, no. 3 (May 1, 2016): 336–39. https://doi.org/10.1002/asmb.2169.
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    • Lin, Lin, Cliburn Chan, and Mike West. “Discriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studies.” Biostatistics 17, no. 1 (January 2016): 40–53. https://doi.org/10.1093/biostatistics/kxv021.
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    • Nakajima, J., and M. West. “Dynamic network signal processing using latent threshold models.” Digital Signal Processing: A Review Journal 47 (December 1, 2015): 5–16. https://doi.org/10.1016/j.dsp.2015.04.008.
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    • Kontoghiorghes, E. J., H. K. Van Dijk, D. A. Belsley, T. Bollerslev, F. X. Diebold, J. M. Dufour, R. Engle, et al. “CFEnetwork: The Annals of computational and financial econometrics: 2nd issue.” Computational Statistics and Data Analysis 76 (January 1, 2014): 1–3. https://doi.org/10.1016/j.csda.2014.04.006.
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    • Kontoghiorghes, Erricos John, Herman K van Dijk, David A. Belsley, Tim Bollerslev, Francis X. Diebold, Jean-Marie Dufour, Robert F. Engle, et al. “CFEnetwork: The Annals of Computational and Financial Econometrics: 2nd Issue.” Comput. Stat. Data Anal. 76 (2014): 1–3. https://doi.org/10.1016/j.csda.2014.04.006.
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    • Mukherjee, C., P. S. Kasibhatla, and M. West. “Spatially-varying SAR models and Bayesian inference for high-resolution lattice data.” Annals of the Institute of Statistical Mathematics 66 (2014): 000–000. https://doi.org/10.1007/s10463-013-0426-9.
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    • Zhou, X., J. Nakajima, and M. West. “Bayesian forecasting and portfolio decisions using dynamic dependent factor models.” International Journal of Forecasting (2014).
    • Zhou, X., J. Nakajima, and M. West. “Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models.” International Journal of Forecasting 30, no. 4 (January 1, 2014): 963–80. https://doi.org/10.1016/j.ijforecast.2014.03.017.
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    • Lin, Lin, Cliburn Chan, Sine R. Hadrup, Thomas M. Froesig, Quanli Wang, and Mike West. “Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies.” Stat Appl Genet Mol Biol 12, no. 3 (June 2013): 309–31. https://doi.org/10.1515/sagmb-2012-0001.
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    • Cron, Andrew, Cécile Gouttefangeas, Jacob Frelinger, Lin Lin, Satwinder K. Singh, Cedrik M. Britten, Marij J. P. Welters, Sjoerd H. van der Burg, Mike West, and Cliburn Chan. “Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.” Plos Comput Biol 9, no. 7 (2013): e1003130. https://doi.org/10.1371/journal.pcbi.1003130.
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    • Nakajima, J., and M. West. “Bayesian analysis of latent threshold dynamic models.” Journal of Business & Economic Statistics 31 (2013): 151–64. https://doi.org/10.1080/07350015.2012.747847.
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    • Manolopoulou, I., M. P. Matheu, M. D. Cahalan, M. West, and T. B. Kepler. “Bayesian spatio-dynamic modeling in cell motility studies: Learning nonlinear taxic fields guiding the immune response.” Journal of the American Statistical Association 107, no. 499 (December 12, 2012): 855–65. https://doi.org/10.1080/01621459.2012.655995.
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    • Manolopoulou, I., M. P. Matheu, M. D. Cahalan, M. West, and T. B. Kepler. “Rejoinder.” Journal of the American Statistical Association 107, no. 499 (December 12, 2012): 871–74. https://doi.org/10.1080/01621459.2012.714715.
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    • Nakajima, J., and M. West. “Dynamic factor volatility modeling: A bayesian latent threshold approach.” Journal of Financial Econometrics 11, no. 1 (December 1, 2012): 116–53. https://doi.org/10.1093/jjfinec/nbs013.
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    • Wang, Quanli, and Mike West. “Model-controlled flooding with applications to image reconstruction and segmentation.” Journal of Electronic Imaging 21, no. 2 (June 2012). https://doi.org/10.1117/1.jei.21.2.023020.
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    • Bonassi, Fernando V., Lingchong You, and Mike West. “Bayesian learning from marginal data in bionetwork models.” Statistical Applications in Genetics and Molecular Biology 10, no. 1 (October 27, 2011). https://doi.org/10.2202/1544-6115.1684.
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    • Hallen, Mark, Bochong Li, Yu Tanouchi, Cheemeng Tan, Mike West, and Lingchong You. “Computation of steady-state probability distributions in stochastic models of cellular networks.” Plos Computational Biology 7, no. 10 (October 13, 2011): e1002209. https://doi.org/10.1371/journal.pcbi.1002209.
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    • Mukherjee, C., P. S. Kasibhatla, and M. West. “Bayesian statistical modeling of spatially correlated error structure in atmospheric tracer inverse analysis.” Atmospheric Chemistry and Physics 11, no. 11 (July 15, 2011): 5365–82. https://doi.org/10.5194/acp-11-5365-2011.
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    • Yao, Guang, Cheemeng Tan, Mike West, Joseph R. Nevins, and Lingchong You. “Origin of bistability underlying mammalian cell cycle entry.” Molecular Systems Biology 7 (April 2011): 485. https://doi.org/10.1038/msb.2011.19.
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    • Cron, Andrew J., and Mike West. “Efficient Classification-Based Relabeling in Mixture Models.” The American Statistician 65, no. 1 (February 2011): 16–20. https://doi.org/10.1198/tast.2011.10170.
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    • Chan, Cliburn, Lin Lin, Jacob Frelinger, Valérie Hérbert, Dominic Gagnon, Claire Landry, Rafick-Pierre Sékaly, et al. “Optimization of a highly standardized carboxyfluorescein succinimidyl ester flow cytometry panel and gating strategy design using discriminative information measure evaluation.” Cytometry A 77, no. 12 (December 2010): 1126–36. https://doi.org/10.1002/cyto.a.20987.
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    • Manolopoulou, I., C. Chan, and M. West. “Rejoinder.” Bayesian Analysis 5, no. 3 (December 1, 2010): 461–64. https://doi.org/10.1214/10-BA517REJ.
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    • Chen, Julia Ling-Yu, Daniel Merl, Christopher W. Peterson, Jianli Wu, Patrick Yantyng Liu, Hanwei Yin, Deborah M. Muoio, Don E. Ayer, Mike West, and Jen-Tsan Chi. “Lactic acidosis triggers starvation response with paradoxical induction of TXNIP through MondoA.” Plos Genet 6, no. 9 (September 2, 2010): e1001093. https://doi.org/10.1371/journal.pgen.1001093.
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    • Niemi, Jarad, and Mike West. “Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.” Journal of Computational and Graphical Statistics : A Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America 19, no. 2 (June 2010): 260–80. https://doi.org/10.1198/jcgs.2010.08117.
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    • Suchard, Marc A., Quanli Wang, Cliburn Chan, Jacob Frelinger, Andrew Cron, and Mike West. “Understanding GPU Programming for Statistical Computation: Studies in Massively Parallel Massive Mixtures.” J Comput Graph Stat 19, no. 2 (June 1, 2010): 419–38. https://doi.org/10.1198/jcgs.2010.10016.
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    • Yoshida, Ryo, and Mike West. “Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing.” Journal of Machine Learning Research : Jmlr 11 (May 2010): 1771–98.
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    • Lin, L., C. Chan, and M. West. “Discriminative information analysis in mixture modelling.” Working Paper, Department of Statistical Science, Duke University, no. 10–23 (2010).
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    • Manolopoulou, I., C. Chan, and M. West. “Selection sampling from large data sets for targeted inference in mixture modeling.” Bayesian Analysis 5, no. 3 (2010): 429–50. https://doi.org/10.1214/10-BA517.
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    • Manolopoulou, Ioanna, Cliburn Chan, and Mike West. “Selection Sampling from Large Data Sets for Targeted Inference in Mixture Modeling.” Bayesian Analysis 5, no. 3 (January 2010): 1–22.
    • Suchard, M. A., C. Holmes, and M. West. “Some of the What?, Why?, How?, Who? and Where? of graphics processing unit computing for Bayesian analysis.” Bulletin of the International Society for Bayesian Analysis 17 (2010): 12–16.
    • Wang, Quanli, Jarad Niemi, Chee-Meng Tan, Lingchong You, and Mike West. “Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.” Cytometry. Part a : The Journal of the International Society for Analytical Cytology 77, no. 1 (January 2010): 101–10. https://doi.org/10.1002/cyto.a.20812.
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    • Yoshida, R., and M. West. “Bayesian learning in sparse graphical factor models via annealed entropy.” Journal of Machine Learning Research 11 (2010): 1771–98.
    • Ji, Chunlin, Daniel Merl, Thomas B. Kepler, and Mike West. “Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology.” Bayesian Analysis 4, no. 2 (December 2009): 297–316. https://doi.org/10.1214/09-ba411.
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    • Liu, F., and M. West. “A dynamic modelling strategy for bayesian computer model emulation.” Bayesian Analysis 4, no. 2 (December 1, 2009): 393–412. https://doi.org/10.1214/09-BA415.
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    • Chang, Jeffrey T., Carlos Carvalho, Seiichi Mori, Andrea H. Bild, Michael L. Gatza, Quanli Wang, Joseph E. Lucas, et al. “A genomic strategy to elucidate modules of oncogenic pathway signaling networks.” Molecular Cell 34, no. 1 (April 2009): 104–14. https://doi.org/10.1016/j.molcel.2009.02.030.
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    • Lucas, J. E., C. M. Carvalho, J. L. Y. Chen, J. T. Chi, and M. West. “Cross-study projections of genomic biomarkers: An evaluation in cancer genomics.” Plos One 4, no. 2 (February 19, 2009). https://doi.org/10.1371/journal.pone.0004523.
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    • Lucas, Joseph E., Carlos M. Carvalho, Julia Ling-Yu Chen, Jen-Tsan Chi, and Mike West. “Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.” Plos One 4, no. 2 (2009): e4523. https://doi.org/10.1371/journal.pone.0004523.
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    • Lucas, Joseph, Carlos Carvalho, and Mike West. “A bayesian analysis strategy for cross-study translation of gene expression biomarkers.” Statistical Applications in Genetics and Molecular Biology 8 (January 2009): Article-11. https://doi.org/10.2202/1544-6115.1436.
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    • Merl, Daniel, Julia Ling-Yu Chen, Jen-Tsan Chi, and Mike West. “AN INTEGRATIVE ANALYSIS OF CANCER GENE EXPRESSION STUDIES USING BAYESIAN LATENT FACTOR MODELING.” Ann Appl Stat 3, no. 4 (2009): 1675–94. https://doi.org/10.1214/09-aoas261.
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    • Mukherjee, C., 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, 1274–87.
    • Wang, H., and M. West. “Bayesian analysis of matrix normal graphical models.” Biometrika 96 (2009): 821–34. https://doi.org/10.1093/biomet/asp049.
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    • Chen, Julia Ling-Yu, Joseph E. Lucas, Thies Schroeder, Seiichi Mori, Jianli Wu, Joseph Nevins, Mark Dewhirst, Mike West, and Jen-Tsan Chi. “The genomic analysis of lactic acidosis and acidosis response in human cancers.” Plos Genet 4, no. 12 (December 2008): e1000293. https://doi.org/10.1371/journal.pgen.1000293.
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    • Chan, Cliburn, Feng Feng, Janet Ottinger, David Foster, Mike West, and Thomas B. Kepler. “Statistical mixture modeling for cell subtype identification in flow cytometry.” Cytometry A 73, no. 8 (August 2008): 693–701. https://doi.org/10.1002/cyto.a.20583.
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    • Goldschmidt-Clermont, Pascal J., Chunming Dong, Mike West, and David M. Seo. “Of cardiovascular illness and diversity of biological response.” Trends in Cardiovascular Medicine 18, no. 5 (July 2008): 194–97. https://doi.org/10.1016/j.tcm.2008.07.003.
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    • Clarke, J., and M. West. “Bayesian Weibull tree models for survival analysis of clinico-genomic data.” Statistical Methodology 5, no. 3 (May 1, 2008): 238–62. https://doi.org/10.1016/j.stamet.2007.09.003.
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    • Carvalho, C. M., 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 103 (2008): 1438–56.
    • Chen, J. L., J. E. Lucas, T. Schroeder, S. Mori, J. Wu, J. R. Nevins, M. Dewhirst, M. West, and J. T. A. Chi. “Genomic analysis of response to lactic acidosis and acidosis in human cancers.” Plos Genetics 4, no. 12 (2008): e1000293.
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    • Xu, M., 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 9 (2008): Supp1:S12-Supp1:S12.
    • Xu, Min, Ming-Chih J. Kao, Juan Nunez-Iglesias, Joseph R. Nevins, Mike West, and Xianghong Jasmine Zhou. “An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer.” Bmc Genomics 9 Suppl 1 (January 2008): S12. https://doi.org/10.1186/1471-2164-9-s1-s12.
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    • Carvalho, C. M., and M. West. “Dynamic matrix-variate graphical models.” Bayesian Analysis 2, no. 1 (December 1, 2007): 69–98. https://doi.org/10.1214/07-BA204.
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    • Liang, F., S. Mukherjee, and M. West. “Understanding the use of unlabelled data in predictive modelling.” Statistical Science 22, no. 2 (October 2007): 189–205.
    • Carvalho, C. M., H. Massam, and M. West. “Simulation of hyper-inverse Wishart distributions in graphical models.” Biometrika 94, no. 3 (September 14, 2007): 647–59. https://doi.org/10.1093/biomet/asm056.
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    • Hans, C., A. Dobra, and M. West. “Shotgun stochastic search for "large p" regression.” Journal of the American Statistical Association 102, no. 478 (June 1, 2007): 507–16. https://doi.org/10.1198/016214507000000121.
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    • Seo, David M., Pascal J. Goldschmidt-Clermont, and Mike West. “Of mice and men: Sparse statistical modeling in cardiovascular genomics.” The Annals of Applied Statistics 1, no. 1 (June 1, 2007). https://doi.org/10.1214/07-aoas110.
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    • Liang, F., S. Mukherjee, and M. West. “The use of unlabeled data in predictive modeling.” Statistical Science 22, no. 2 (May 1, 2007): 189–205. https://doi.org/10.1214/088342307000000032.
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    • Wu, Y., H. Tjelmeland, and M. West. “Bayesian CART: Prior specification and posterior simulation.” Journal of Computational and Graphical Statistics 16, no. 1 (March 1, 2007): 44–66. https://doi.org/10.1198/106186007X180426.
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    • Carvalho, C. M., and M. West. “Dynamic matrix-variate graphical models.” Bayesian Analysis 2 (2007): 69–98.
    • Hans, C., A. Dobra, and M. West. “Shotgun stochastic search in regression with many predictors.” Journal of the American Statistical Association 102 (2007): 507–16.
    • Hans, C., Q. Wang, A. Dobra, and M. West. “SSS: High-dimensional Bayesian regression model search.” Bulletin of the International Society for Bayesian Analysis 24 (2007): 8–9.
    • Liang, F., K. Mao, M. Liao, S. Mukherjee, and M. West. “Non-parametric Bayesian kernel models.” Department of Statistical Science, Duke University, 2007.
    • Wang, Q., C. M. Carvalho, J. E. Lucas, and M. West. “BFRM: Bayesian factor regression modelling.” Bulletin of the International Society for Bayesian Analysis 14 (2007): 4–5.
    • Wu, Y., H. Tjelmeland, and M. West. “Bayesian CART: Prior structure and MCMC computations.” Journal of Computational and Graphical Statistics 16 (2007): 44–66.
    • Ferreira, M. A. R., M. West, H. K. H. Lee, and D. M. Higdon. “Multi-scale and hidden resolution time series models.” Bayesian Analysis 1, no. 4 (December 1, 2006): 947–68. https://doi.org/10.1214/06-BA131.
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    • Cheng, Skye H., Cheng-Fang Horng, Mike West, Erich Huang, Jennifer Pittman, Mei-Hua Tsou, Holly Dressman, et al. “Genomic prediction of locoregional recurrence after mastectomy in breast cancer.” J Clin Oncol 24, no. 28 (October 1, 2006): 4594–4602. https://doi.org/10.1200/JCO.2005.02.5676.
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    • West, Mike, Geoffrey S. Ginsburg, Andrew T. Huang, and Joseph R. Nevins. “Embracing the complexity of genomic data for personalized medicine.” Genome Res 16, no. 5 (May 2006): 559–66. https://doi.org/10.1101/gr.3851306.
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    • Cheng, Skye Hongiun, Cheng-Fang Horng, Jennifer L. Clarke, Mei-Hua Tsou, Stella Y. Tsai, Chii-Ming Chen, James J. Jian, et al. “Prognostic index score and clinical prediction model of local regional recurrence after mastectomy in breast cancer patients.” Int J Radiat Oncol Biol Phys 64, no. 5 (April 1, 2006): 1401–9. https://doi.org/10.1016/j.ijrobp.2005.11.015.
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    • Dobra, A., C. Tebaldi, and M. West. “Data augmentation in multi-way contingency tables with fixed marginal totals.” Journal of Statistical Planning and Inference 136, no. 2 (February 1, 2006): 355–72. https://doi.org/10.1016/j.jspi.2004.07.002.
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    • Dressman, Holly K., Christopher Hans, Andrea Bild, John A. Olson, Eric Rosen, P Kelly Marcom, Vlayka B. Liotcheva, et al. “Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant chemotherapy.” Clin Cancer Res 12, no. 3 Pt 1 (February 1, 2006): 819–26. https://doi.org/10.1158/1078-0432.CCR-05-1447.
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    • Bild, Andrea H., Guang Yao, Jeffrey T. Chang, Quanli Wang, Anil Potti, Dawn Chasse, Mary-Beth Joshi, et al. “Oncogenic pathway signatures in human cancers as a guide to targeted therapies.” Nature 439, no. 7074 (January 19, 2006): 353–57. https://doi.org/10.1038/nature04296.
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    • Ferreira, M. A. R., M. West, H. K. H. Lee, and D. M. Higdon. “Multiscale and hidden resolution time series models.” Bayesian Analysis 2 (2006): 294–314.
    • Hans, C., and M. West. “High-dimensional regression in cancer genomics.” Bulletin of the International Society for Bayesian Analysis 13 (2006): 2–3.
    • Karra, R., S. Vemullapalli, C. Dong, E. E. Herderick, X. Song, K. Slosek, J. R. Nevins, M. West, P. J. Goldschmidt-Clermont, and D. Seo. “Stem Cells of Aging Donors- Insufficient Capacity to Repair Causes & Progression of Atherosclerosis in the Recipient.” Journal of the American Society of Nephrology 17 (2006): 317–22.
    • Jones, B., and M. West. “Covariance decomposition in undirected Gaussian graphical models.” Biometrika 92, no. 4 (December 1, 2005): 779–86. https://doi.org/10.1093/biomet/92.4.779.
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    • Karra, Ravi, Sreekanth Vemullapalli, Chunming Dong, Edward E. Herderick, Xiaohua Song, Kathy Slosek, Joseph R. Nevins, Mike West, Pascal J. Goldschmidt-Clermont, and David Seo. “Molecular evidence for arterial repair in atherosclerosis.” Proc Natl Acad Sci U S A 102, no. 46 (November 15, 2005): 16789–94. https://doi.org/10.1073/pnas.0507718102.
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    • Black, Esther P., Timothy Hallstrom, Holly K. Dressman, Mike West, and Joseph R. Nevins. “Distinctions in the specificity of E2F function revealed by gene expression signatures.” Proc Natl Acad Sci U S A 102, no. 44 (November 1, 2005): 15948–53. https://doi.org/10.1073/pnas.0504300102.
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    • Jones, B., C. Carvalho, A. Dobra, C. Hans, C. Carter, and M. West. “Experiments in stochastic computation for high-dimensional graphical models.” Statistical Science 20, no. 4 (November 1, 2005): 388–400. https://doi.org/10.1214/088342305000000304.
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    • Delong, Mark, Guang Yao, Quanli Wang, Adrian Dobra, Esther P. Black, Jeffrey T. Chang, Andrea Bild, Mike West, Joseph R. Nevins, and Holly Dressman. “DIG--a system for gene annotation and functional discovery.” Bioinformatics 21, no. 13 (July 1, 2005): 2957–59. https://doi.org/10.1093/bioinformatics/bti467.
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    • Petersen, R. P., A. Bild, H. Dressman, M. M. Joshi, D. H. Conlon, M. West, J. R. Nevins, and D. H. Harpole. “Gene expression signatures for prognosis in NSCLC, coupled with signatures of oncogenic pathway deregulation, provide a novel approach for selection of molecular targets.” J Clin Oncol 23, no. 16_suppl (June 2005): 7020.
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    • Berchuck, Andrew, Edwin S. Iversen, Johnathan M. Lancaster, Jennifer Pittman, Jingqin Luo, Paula Lee, Susan Murphy, et al. “Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers.” Clin Cancer Res 11, no. 10 (May 15, 2005): 3686–96. https://doi.org/10.1158/1078-0432.CCR-04-2398.
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    • Rich, Jeremy N., Christopher Hans, Beatrix Jones, Edwin S. Iversen, Roger E. McLendon, BK Ahmed Rasheed, Adrian Dobra, et al. “Gene expression profiling and genetic markers in glioblastoma survival.” Cancer Res 65, no. 10 (May 15, 2005): 4051–58. https://doi.org/10.1158/0008-5472.CAN-04-3936.
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    • Pittman, Jennifer, Erich Huang, Joseph Nevins, Quanli Wang, and Mike West. “Bayesian analysis of binary prediction tree models for retrospectively sampled outcomes.” Biostatistics 5, no. 4 (October 2004): 587–601. https://doi.org/10.1093/biostatistics/kxh011.
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    • Seo, David, Tao Wang, Holly Dressman, Edward E. Herderick, Edwin S. Iversen, Chunming Dong, Korkut Vata, et al. “Gene expression phenotypes of atherosclerosis.” Arterioscler Thromb Vasc Biol 24, no. 10 (October 2004): 1922–27. https://doi.org/10.1161/01.ATV.0000141358.65242.1f.
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    • Huang, Erich S., Joseph R. Nevins, Mike West, and Paul C. Kuo. “An overview of genomic data analysis.” Surgery 136, no. 3 (September 2004): 497–99. https://doi.org/10.1016/j.surg.2004.05.037.
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    • Pittman, Jennifer, Erich Huang, Holly Dressman, Cheng-Fang Horng, Skye H. Cheng, Mei-Hua Tsou, Chii-Ming Chen, et al. “Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes.” Proc Natl Acad Sci U S A 101, no. 22 (June 1, 2004): 8431–36. https://doi.org/10.1073/pnas.0401736101.
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    • Berchuck, Andrew, Edwin S. Iversen, Johnathan M. Lancaster, Holly K. Dressman, Mike West, Joseph R. Nevins, and Jeffrey R. Marks. “Prediction of optimal versus suboptimal cytoreduction of advanced-stage serous ovarian cancer with the use of microarrays.” Am J Obstet Gynecol 190, no. 4 (April 2004): 910–25. https://doi.org/10.1016/j.ajog.2004.02.005.
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    • Godsill, S. J., A. Doucet, and M. West. “Monte carlo smoothing for nonlinear time series.” Journal of the American Statistical Association 99, no. 465 (March 1, 2004): 156–68. https://doi.org/10.1198/016214504000000151.
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    • Dobra, A., C. Hans, B. Jones, J. R. Nevins, G. Yao, and M. West. “Sparse graphical models for exploring gene expression data.” Journal of Multivariate Analysis 90, no. 1 SPEC. ISS. (January 1, 2004): 196–212. https://doi.org/10.1016/j.jmva.2004.02.009.
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    • Hoffman, E. P., T. Awad, A. Spira, J. Palma, T. Webster, G. Wright, J. Buckley, et al. “Expression profiling: Best practices for Affymetrix array data generation and interpretation for clinical trials.” Nature Reviews Genetics 5 (2004): 229–37.
    • Lopes, H. F., and M. West. “Bayesian model assessment in factor analysis.” Statistica Sinica 14, no. 1 (January 1, 2004): 41–67.
    • Nevins, Joseph R., Erich S. Huang, Holly Dressman, Jennifer Pittman, Andrew T. Huang, and Mike West. “Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction.” Hum Mol Genet 12 Spec No 2 (October 15, 2003): R153–57. https://doi.org/10.1093/hmg/ddg287.
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    • Huang, Erich S., Esther P. Black, Holly Dressman, Mike West, and Joseph R. Nevins. “Gene expression phenotypes of oncogenic signaling pathways.” Cell Cycle 2, no. 5 (September 2003): 415–17.
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    • Huang, E., S. Ishida, J. Pittmann, H. Dressman, A. Bild, M. Kloos, M. D’Amico, R. G. Pestell, M. West, and J. R. Nevins. “Erratum: Gene expression phenotypic models that predict the activity of oncogenic pathways (Nature Genetics (2003) 34 (226-230)).” Nature Genetics 34, no. 4 (August 1, 2003): 465. https://doi.org/10.1038/ng0803-465.
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    • Black, Esther P., Erich Huang, Holly Dressman, Rachel Rempel, Nina Laakso, Sylvia L. Asa, Seiichi Ishida, Mike West, and Joseph R. Nevins. “Distinct gene expression phenotypes of cells lacking Rb and Rb family members.” Cancer Res 63, no. 13 (July 1, 2003): 3716–23.
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    • Huang, Erich, Seiichi Ishida, Jennifer Pittman, Holly Dressman, Andrea Bild, Mark Kloos, Mark D’Amico, Richard G. Pestell, Mike West, and Joseph R. Nevins. “Gene expression phenotypic models that predict the activity of oncogenic pathways.” Nat Genet 34, no. 2 (June 2003): 226–30. https://doi.org/10.1038/ng1167.
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    • Huang, Erich, Skye H. Cheng, Holly Dressman, Jennifer Pittman, Mei Hua Tsou, Cheng Fang Horng, Andrea Bild, et al. “Gene expression predictors of breast cancer outcomes.” Lancet 361, no. 9369 (May 10, 2003): 1590–96. https://doi.org/10.1016/S0140-6736(03)13308-9.
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    • Paddock, S. M., F. Ruggeri, M. Lavine, and M. West. “Randomized Polya tree models for nonparametric Bayesian inference.” Statistica Sinica 13, no. 2 (April 1, 2003): 443–60.
    • Huang, Erich, Mike West, and Joseph R. Nevins. “Gene expression profiling for prediction of clinical characteristics of breast cancer.” Recent Prog Horm Res 58 (2003): 55–73. https://doi.org/10.1210/rp.58.1.55.
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    • Paddock, S., F. Ruggeri, M. Lavine, and M. West. “Tree models for nonparametric Bayesian inference.” Statistica Sinica 13 (2003): 443–60.
    • Pittman, J., E. S. Huang, J. R. Nevins, and M. West. “Prediction tree models in clinico-genomics.” Bulletin of the International Statistical Institute 54 (2003): 76–76.
    • Fong, W., S. J. Godsill, A. Doucet, and M. West. “Monte Carlo smoothing with application to audio signal enhancement.” Ieee Transactions on Signal Processing 50, no. 2 (February 1, 2002): 438–49. https://doi.org/10.1109/78.978397.
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    • Lee, H. K. H., D. M. Higdon, Z. Bi, M. A. R. Ferreira, and M. West. “Markov random field models for high-dimensional parameters in simulations of fluid flow in porous media.” Technometrics 44, no. 3 (January 1, 2002): 230–41. https://doi.org/10.1198/004017002188618419.
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    • Spang, Rainer, Harry Zuzan, Mike West, Joseph Nevins, Carrie Blanchette, and Jeffrey R. Marks. “Prediction and uncertainty in the analysis of gene expression profiles.” In Silico Biol 2, no. 3 (2002): 369–81.
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    • Tebaldi, C., M. West, and A. F. Karr. “Statistical analyses of freeway traffic flows.” Journal of Forecasting 21, no. 1 (January 1, 2002): 39–68. https://doi.org/10.1002/for.804.
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    • West, M., C. Blanchette, H. Dressman, E. Huang, S. Ishida, R. Spang, H. Zuzan, J. A. Olson, J. R. Marks, and J. R. Nevins. “Predicting the clinical status of human breast cancer by using gene expression profiles.” Proc Natl Acad Sci U S A 98, no. 20 (September 25, 2001): 11462–67. https://doi.org/10.1073/pnas.201162998.
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    • Ishida, S., 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.” Mol Cell Biol 21, no. 14 (July 2001): 4684–99. https://doi.org/10.1128/MCB.21.14.4684-4699.2001.
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    • Godsill, Simon, Arnaud Doucet, and Mike West. “Maximum a posteriori sequence estimation using Monte Carlo particle filters.” Annals of the Institute of Statistical Mathematics 53, no. 1 (2001): 82–96. https://doi.org/10.1023/a:1017968404964.
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    • Prado, R., G. Huerta, and M. West. “Bayesian time-varying autoregressions: Theory, methods and applications.” Resenhas 4 (2001): 405–22.
    • Prado, R., M. West, and A. D. Krystal. “Multi-channel EEG analyses via dynamic regression models with time-varying lag/lead structure.” Journal of the Royal Statistical Society (Ser. C) 50 (2001): 95–110.
    • Prado, R., M. West, and A. D. Krystal. “Multichannel electroencephalographic analyses via dynamic regression models with time-varying lag-lead structure.” Journal of the Royal Statistical Society. Series C: Applied Statistics 50, no. 1 (January 1, 2001): 95–109. https://doi.org/10.1111/1467-9876.00222.
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    • Spang, R., 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 2 (2001): 0033–0033.
    • Huerta, G., and M. West. “Priors and component structures in autoregressive time series models.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 62, no. 2 (May 2000): 429–429. https://doi.org/10.1111/1467-9868.00241.
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    • Aguilar, O., and M. West. “Bayesian dynamic factor models and portfolio allocation.” Journal of Business and Economic Statistics 18, no. 3 (January 1, 2000): 338–57. https://doi.org/10.1080/07350015.2000.10524875.
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    • Burgess, J., V. Lourdes, and M. West. “Profiling mental health provider trends in health care delivery systems.” Health Services & Outcomes Research Methodology 100 (2000): 253–76.
    • Doucet, A., S. J. Godsill, and M. West. “Monte Carlo filtering and smoothing with application to time-varying spectral estimation.” Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing  Proceedings 2 (January 1, 2000): 701–4. https://doi.org/10.1109/ICASSP.2000.859056.
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    • Krystal, A. D., M. West, R. Prado, H. Greenside, S. Zoldi, and R. D. Weiner. “EEG effects of ECT: implications for rTMS.” Depress Anxiety 12, no. 3 (2000): 157–65. https://doi.org/10.1002/1520-6394(2000)12:3<157::AID-DA7>3.0.CO;2-R.
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    • Krystal, A. D., R. Prado, and M. West. “New methods of time series analysis of non-stationary EEG data: eigenstructure decompositions of time varying autoregressions.” Clin Neurophysiol 110, no. 12 (December 1999): 2197–2206. https://doi.org/10.1016/s1388-2457(99)00165-0.
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    • West, M., R. Prado, and A. D. Krystal. “Evaluation and Comparison of EEG Traces: Latent Structure in Nonstationary Time Series.” Journal of the American Statistical Association 94, no. 448 (December 1, 1999): 1083–95. https://doi.org/10.1080/01621459.1999.10473861.
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    • West, M., R. Prado, and A. D. Krystal. “Evaluation and Comparison of EEG Traces: Latent Structure in Nonstationary Time Series.” Journal of the American Statistical Association 94, no. 446 (June 1, 1999): 375–87. https://doi.org/10.1080/01621459.1999.10474128.
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    • Huerta, G., and M. West. “Bayesian inference on periodicities and component spectral structure in time series.” Journal of Time Series Analysis 20, no. 4 (January 1, 1999): 401–16. https://doi.org/10.1111/1467-9892.00145.
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    • Huerta, G., and M. West. “Priors and component structures in autoregressive time series models.” Journal of the Royal Statistical Society. Series B: Statistical Methodology 61, no. 4 (January 1, 1999): 881–99. https://doi.org/10.1111/1467-9868.00208.
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    • Krystal, A. D., R. Prado, and M. West. “New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions.” Clinical Neurophysiology 110 (1999): 1–10.
    • West, M. “Time-frequency decompositions: Bayesian model-based approaches.” Conference Record of the Asilomar Conference on Signals, Systems and Computers 1 (December 1, 1998): 276.
    • Tebaldi, C., and M. West. “Rejoinder.” Journal of the American Statistical Association 93, no. 442 (June 1, 1998): 576–576. https://doi.org/10.1080/01621459.1998.10473710.
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    • Tebaldi, C., and M. West. “Bayesian inference on network traffic using link count data.” Journal of the American Statistical Association 93, no. 442 (June 1, 1998): 557–73. https://doi.org/10.1080/01621459.1998.10473707.
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    • Huerta, G., and M. West. “Bayesian inference for unequally-spaced time series.” Jsm Proceedings,Section on Bayesian Statistical Science. Alexandria, Va: American Statistical Association, 1998, 17–21.
    • Tebaldi, C., and M. West. “Bayesian inference on network traffic using link count data (with discussion).” Journal of the American Statistical Association 93 (1998): 557–76.
    • Cargnoni, C., P. Müller, and M. West. “Bayesian Forecasting of Multinomial Time Series through Conditionally Gaussian Dynamic Models.” Journal of the American Statistical Association 92, no. 438 (June 1, 1997): 640–47. https://doi.org/10.1080/01621459.1997.10474015.
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    • West, M. “Hierarchical Mixture Models in Neurological Transmission Analysis.” Journal of the American Statistical Association 92, no. 438 (June 1, 1997): 587–606. https://doi.org/10.1080/01621459.1997.10474011.
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    • Turner, D. A., Y. Chen, J. T. Isaac, M. West, and H. V. Wheal. “Excitatory synaptic site heterogeneity during paired pulse plasticity in CA1 pyramidal cells in rat hippocampus in vitro.” J Physiol 500 ( Pt 2) (April 15, 1997): 441–61. https://doi.org/10.1113/jphysiol.1997.sp022032.
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    • Cao, G., and M. West. “Computing distributions of order statistics.” Communications in Statistics  Theory and Methods 26, no. 3 (January 1, 1997): 755–64. https://doi.org/10.1080/03610929708831947.
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    • Müller, P., M. West, and S. Maceachern. “Bayesian models for non-linear autoregressions.” Journal of Time Series Analysis 18, no. 6 (January 1, 1997): 593–614. https://doi.org/10.1111/1467-9892.00070.
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    • Robert, C. P., M. Aitkin, D. R. Cox, M. Stephens, A. Polymenis, W. R. Gilks, A. Nobile, et al. “On Bayesian analysis of mixtures with an unknown number of components - Discussion.” Journal of the Royal Statistical Society Series B Statistical Methodology 59, no. 4 (January 1, 1997): 758–92.
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    • Turner, D. A., 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 500 (1997): 441–61.
    • West, M. “Time series decomposition.” Biometrika 84, no. 2 (January 1, 1997): 489–94. https://doi.org/10.1093/biomet/84.2.489.
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    • Cao, G., and M. West. “Practical Bayesian inference using mixtures of mixtures.” Biometrics 52, no. 4 (December 1996): 1334–41. https://doi.org/10.2307/2532848.
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    • Müller, P., A. Erkanli, and M. West. “Bayesian curve fitting using multivariate normal mixtures.” Biometrika 83, no. 1 (January 1, 1996): 67–79. https://doi.org/10.1093/biomet/83.1.67.
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    • West, M. “Inference in successive sampling discovery models.” Journal of Econometrics 75, no. 1 (January 1, 1996): 217–38. https://doi.org/10.1016/0304-4076(95)01777-1.
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    • West, Mike. “Bayesian Inference in Cyclical Component Dynamic Linear Models.” Journal of the American Statistical Association 90, no. 432 (December 1995): 1301–1301. https://doi.org/10.2307/2291520.
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    • Escobar, Michael D., and Mike West. “Bayesian Density Estimation and Inference Using Mixtures.” Journal of the American Statistical Association 90, no. 430 (June 1995): 577–577. https://doi.org/10.2307/2291069.
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    • Escobar, M. D., and M. West. “Bayesian density estimation and inference using mixtures.” Journal of the American Statistical Association 90, no. 430 (January 1, 1995): 577–88. https://doi.org/10.1080/01621459.1995.10476550.
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    • West, M. “Bayesian inference in cyclical component dynamic linear models.” Journal of the American Statistical Association 90, no. 432 (January 1, 1995): 1301–12. https://doi.org/10.1080/01621459.1995.10476634.
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    • West, Mike, and Dennis A. Turner. “Deconvolution of Mixtures in Analysis of Neural Synaptic Transmission.” The Statistician 43, no. 1 (1994): 31–31. https://doi.org/10.2307/2348930.
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    • Turner, D. A., and M. West. “Bayesian analysis of mixtures applied to post-synaptic potential fluctuations.” J Neurosci Methods 47, no. 1–2 (April 1993): 1–21. https://doi.org/10.1016/0165-0270(93)90017-l.
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    • Turner, D. A., and M. West. “Statistical analysis of mixtures applied to postsynaptic potential fluctuations.” Journal of Neuroscience Methods 47 (1993): 1–23.
    • WEST, M. “APPROXIMATING POSTERIOR DISTRIBUTIONS BY MIXTURES.” Journal of the Royal Statistical Society Series B Methodological 55, no. 2 (January 1, 1993): 409–22.
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    • West, M. “Approximating posterior distributions by mixtures.” Journal of the Royal Statistical Society (Ser. B) 54 (1993): 553–68.
    • West, M. “Mixture models, Monte Carlo, Bayesian updating and dynamic models.” Computing Science and Statistics 24 (1993): 325–33.
    • Lavine, M., and M. West. “A Bayesian method for classification and discrimination.” Canadian Journal of Statistics 20, no. 4 (January 1, 1992): 451–61. https://doi.org/10.2307/3315614.
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    • WEST, M. “MODELING AGENT FORECAST DISTRIBUTIONS.” Journal of the Royal Statistical Society Series B Methodological 54, no. 2 (January 1, 1992): 553–67.
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    • WEST, M., and J. CROSSE. “MODELING PROBABILISTIC AGENT OPINION.” Journal of the Royal Statistical Society Series B Methodological 54, no. 1 (January 1, 1992): 285–99.
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    • Harrison, J., and M. West. “Dynamic linear model diagnostics.” Biometrika 78, no. 4 (December 1, 1991): 797–808. https://doi.org/10.1093/biomet/78.4.797.
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    • WEST, M., and R. L. WINKLER. “DATA-BASE ERROR TRAPPING AND PREDICTION.” Journal of the American Statistical Association 86, no. 416 (December 1991): 987–96. https://doi.org/10.2307/2290515.
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    • West, M. “Kernel density estimation and marginalization consistency.” Biometrika 78, no. 2 (June 1, 1991): 421–25. https://doi.org/10.1093/biomet/78.2.421.
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    • Pole, A., and M. West. “Efficient bayesian learning in non‐linear dynamic models.” Journal of Forecasting 9, no. 2 (January 1, 1990): 119–36. https://doi.org/10.1002/for.3980090205.
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    • Pole, A., and M. West. “REFERENCE ANALYSIS OF THE DYNAMIC LINEAR MODEL.” Journal of Time Series Analysis 10, no. 2 (January 1, 1989): 131–47. https://doi.org/10.1111/j.1467-9892.1989.tb00020.x.
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    • Pole, A., and M. West. “Reference analysis of the DLM.” Journal of Time Series Analysis 10 (1989): 131–47.
    • West, M., and P. J. Harrison. “Subjective intervention in formal models.” Journal of Forecasting 8 (1989): 33–53.
    • West, Mike. “Bayesian statistics two: Proceedings of the second Valencia international meeting on Bayesian statistics.” International Journal of Forecasting 4, no. 4 (January 1988): 609–11. https://doi.org/10.1016/0169-2070(88)90138-0.
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    • GAMERMAN, D., and M. WEST. “AN APPLICATION OF DYNAMIC SURVIVAL MODELS IN UNEMPLOYMENT STUDIES.” Journal of the Royal Statistical Society Series D the Statistician 36, no. 2–3 (January 1, 1987): 269–74.
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    • Gamerman, D., and M. West. “A time series application of dynamic survival models in unemployment studies.” The Statistician 36 (1987): 269–74.
    • Harrison, P. J., and M. West. “Practical Bayesian forecasting.” The Statistician 36 (1987): 115–25.
    • Quintana, J. M., and M. West. “An analysis of international exchange rates using multivariate DLMs.” The Statistician 36 (1987): 275–81.
    • West, M. “On scale mixtures of normal distributions.” Biometrika 74 (1987): 646–48.
    • West, M., P. J. Harrison, and A. Pole. “BATS: Bayesian Analysis of Time Series.” The Professional Statistician 6 (1987): 43–46.
    • West, Mike. “Discussion: Influence Functionals for Time Series.” The Annals of Statistics 14, no. 3 (September 1, 1986). https://doi.org/10.1214/aos/1176350036.
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    • West, M. “Bayesian model monitoring.” Journal of the Royal Statistical Society (Ser. B) 48 (1986): 70–78.
    • West, M. “Discussion of: Influence functionals for time series.” Annals of Statistics 14 (1986): 838–40.
    • West, M., and P. J. Harrison. “Monitoring and adaptation in Bayesian forecasting models.” Journal of the American Statistical Association 81, no. 395 (January 1, 1986): 741–50. https://doi.org/10.1080/01621459.1986.10478331.
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    • West, M., and P. J. Harrison. “Monitoring and adaptation in Bayesian forecasting models.” Journal of the American Statistical Association 81 (1986): 741–50.
    • HARRISON, P. J., and M. WEST. “ASPECTS OF BAYESIAN FORECASTING.” Journal of the Operational Research Society 36, no. 12 (January 1, 1985): 1155–1155.
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    • West, M., P. Harrison, and H. S. Migon. “Dynamic generalised linear models and Bayesian forecasting (with discussion).” Journal of the American Statistical Association 80 (1985): 73–97.
    • West, M., P. J. Harrison, and H. S. Migon. “Dynamic generalized linear models and Bayesian forecasting.” Journal of the American Statistical Association 80, no. 389 (January 1, 1985): 73–83. https://doi.org/10.1080/01621459.1985.10477131.
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    • West, M., P. J. Harrison, and H. S. Migon. “Rejoinder.” Journal of the American Statistical Association 80, no. 389 (January 1, 1985): 96–97. https://doi.org/10.1080/01621459.1985.10477139.
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    • West, M. “Outlier models and prior distributions in Bayesian linear regression.” Journal of the Royal Statistical Society (Ser. B) 46 (1984): 431–39.
    • West, M. “Bayesian aggregation.” Journal of the Royal Statistical Society (Ser. A) 147 (1984): 600–607.
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    • Smith, A. F. M., M. West, K. Gordon, M. S. Knapp, and I. Trimble. “Monitoring kidney transplant patients.” The Statistician 32 (1983): 46–54.
    • Smith, A. F. M., and M. West. “Monitoring renal transplants: An application of the multi-process Kalman filter.” Biometrics 39 (1983): 867–78.
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    • Trimble, I., M. West, M. S. Knapp, R. Pownall, and A. F. M. Smith. “Detection of renal allograft rejection by computer.” British Medical Journal 286 (1983): 1695–99.
    • Knapp, M. S., I. Trimble, R. Pownall, M. West, and A. Smith. “The detection of sudden change in renal function by time-series analysis, including the use of the Kalman Filter - a new statistical approach with potential applications for chronobiologists.” Advances in the Biosciences 41, no. C (December 1, 1982): 369–73.
    • West, M. “Robust sequential approximate Bayesian estimation.” Journal of the Royal Statistical Society (Ser. B) 43 (1981): 157–66.
    • Bonassi, Fernando V., Cliburn Chan, and Mike West. “Bayesian analysis of immune response dynamics with sparse time series data,” n.d.
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    • Lavine, Isaac, Andrew Cron, and Mike West. “Bayesian Computation in Dynamic Latent Factor Models,” n.d.
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    • Lavine, Isaac, Michael Lindon, and Mike West. “Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models,” n.d.
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    • West, Mike. “Perspectives on Constrained Forecasting,” n.d.
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    • Yanchenko, Anna K., Graham Tierney, Joseph Lawson, Christoph Hellmayr, Andrew Cron, and Mike West. “Multivariate Dynamic Modeling for Bayesian Forecasting of Business Revenue,” n.d.
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  • Book Sections

    • West, M. “Bayesian dynamic modelling.” In Bayesian Theory and Applications, edited by P. Damien, P. Dellaportes, N. G. Polson, and D. A. Stephens, 145–66. Clarendon: Oxford University Press, 2013.
    • Bernardo, J. M., M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, and M. West. “Preface,” Vol. 9780199694587, 2012. https://doi.org/10.1093/acprof:oso/9780199694587.002.0004.
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    • Merl, D., 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, 118–54. Oxford University Press, 2010.
    • Hyland, R., R. S. Obach, C. Stoner, M. West, M. R. Wester, K. Youdim, and M. Zientek. “Drug-drug interactions: Screening for liability and assessment of risk.” In Hit and Lead Profiling: Identification and Optimization of Drug-like Molecules, 43:165–96, 2010. https://doi.org/10.1002/9783527627448.ch8.
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    • Lucas, J. E., 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, p293-316. Taylor-Francis, 2010.
    • Shen, H., 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, 285–302. New York: Springer-Verlag, 2010.
    • West, M. “Bayesian forecasting.” In Methods and Applications of Statistics in Business, Finance and Management Science, edited by N. Balakrishnan, p72-84. Wiley, 2010.
    • Lucas, J. E., C. M. Carvalho, Q. Wang, A. H. 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, 155–76. Cambridge University Press, 2006.
    • Patil, P. G., M. West, H. V. Wheal, and D. A. Turner. “Physiological and statistical approaches to modeling of synaptic responses.” In Modeling in the Neurosciences: From Biological Systems to Neuromimetic Robotics, 61–88, 2005.
    • Liu, J., and M. West. “Combined parameter and state estimation in simulation-based filtering.” In Sequential Monte Carlo Methods in Practice, edited by A. Doucet, JFG De Freitas, and N. J. Gordon, 197–217. New York: Springer-Verlag, 2001.
    • Krystal, A. D., 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. New York: Novascience, 1999.
    • Turner, D. A., 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, 39–78. London, Gordon & Breach Publishers, 1999.
    • Escobar, M. D., and M. West. “Computing nonparametric hierarchical models.” In Practical Non and Semiparametric Bayesian Statistics, edited by P. Müller, D. D. Dey, and D. Sinha, 1–16. Springer-Verlag, 1998.
    • Paddock, S., M. A. Clyde, and M. West. “Mixture models in the exploration of structure-activity relationships in drug design.” In Bayesian Statistics in Science and Engineering: Case Studies IV, edited by C. Gastonis, R. E. Kass, B. Carlin, A. Carriquiry, A. German, M. West, and I. Verdinelli, 339–53. Springer, 1998. https://doi.org/10.1007/978-1-4612-1502-8_9.
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    • Paddock, S., M. A. Clyde, and M. West. “Mixture models in the exploration of structure-activity relationships in drug design.” In Bayesian Statistics in Science and Engineering: Case Studies IV, edited by C. Gastonis, R. E. Kass, B. Carlin, A. Carriquiry, A. German, M. West, and I. Verdinelli, 339–53. Springer, 1998. https://doi.org/10.1007/978-1-4612-1502-8_9.
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    • West, M. “Bayesian forecasting.” In Encyclopedia of Statistical Sciences, edited by S. Kotz, C. B. Read, and D. L. Banks, 50–60. Wiley, 1998.
    • Prado, R., and M. West. “Exploratory modelling of multiple non-stationary time series: Latent process structure and decompositions.” In Modelling Longitudinal and Spatially Correlated Data, edited by T. Gregoire, 349–62. Springer-Verlag, 1997.
    • West, M., 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, edited by A. F. M. Smith and P. R. Freeman, 363–86. London: Wiley, 1994.

  • Reports

    • Gruber, L. F., and M. West. “GPU-accelerated Bayesian learning in simultaneous graphical dynamic linear models.” Department of Statistical Science, Duke University: Carnegie Mellon University, 2016. https://doi.org/10.1214/15-BA946.
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    • Bonassi, F. V., and M. West. “Sequential monte carlo with adaptive weights for approximate bayesian computation,” January 1, 2015. https://doi.org/10.1214/14-BA891.
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    • Bonassi, F. V., C. Chan, and M. West. “Bayesian computation for immune response modeling with sparse time series data.” Department of Statistical Science, Duke University, May 15, 2014.
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    • Nakajima, J., and M. West. “Sparse and dynamic transfer response factor models via Bayesian latent thresholding.” Department of Statistical Science, Duke University, June 2013.
    • Fox, E. B., and M. West. “Autoregressive models for variance matrices: Stationary inverse Wishart processes.” Department of Statistical Science, Duke University, 2013.
    • Lin, L., C. Chan, and M. West. “Discriminative variable subsets in Bayesian classification with mixture models.” Department of Statistical Science, Duke University, 2013.
    • Xie, M., and M. West. “Dynamic discounting for model mixing in Bayesian forecasting.” Department of Statistical Science, Duke University, 2013.
    • Cron, A. J., and M. West. “Models of random sparse eigenmatrices matrices with application to Bayesian factor analysis.” Department of Statistical Science, Duke University, 2012.
    • Ji, C., H. Shen, and M. West. “Bounded approximations for marginal likelihoods.” Department of Statistical Science, Duke University, 2010.
    • Manolopoulou, I., 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.” Department of Statistical Science, Duke University, 2010.
    • Merl, D., and M. West. “Hierarchical nonparametric mixture models.” Department of Statistical Science, Duke University, 2009.
    • Reeson, C., C. M. Carvalho, and M. West. “Dynamic graphical models and portfolio allocations for structured mutual funds.” Department of Statistical Science, Duke University, 2009.
    • Wang, Q., L. You, and M. West. “CellTracer: Software for automated image segmentation and lineage mapping for single-cell studies.” Department of Statistical Science, Duke University, 2008.
    • Ferreira, M. A. R., D. M. Higdon, H. K. H. Lee, and M. West. “Multi-scale random field models.” Institute of Statistics and Decision Sciences, Duke University, 2005.
    • West, M. “Statistical inference for gravity models in transportation flow forecasting.” Duke University, 1994.

  • Conference Papers

    • Cron, A., and M. West. “Models of random sparse eigenmatrices and Bayesian analysis of multivariate structure.” In Abel Symposia, 11:125–53, 2016. https://doi.org/10.1007/978-3-319-27099-9_7.
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    • Bernardo, J. M., M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, and M. West. “Bayesian Statistics 9.” In Bayesian Statistics 9, 9780199694587:1–720, 2012. https://doi.org/10.1093/acprof:oso/9780199694587.001.0001.
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    • Julia, Mike, Ling-Yu Chen, Joseph E. Lucas, Thies Schroeder, Seiichi Mori, Jianli Wu, Joseph Nevins, Mark Dewhirst, Mike West, and Jen-Tsan Chi. “The genomic analysis of lactic acidosis and acidosis response in human cancers.” In Cancer Research, Vol. 69, 2009.
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    • Bild, A. H., G. Yao, J. T. Chang, Q. L. Wang, A. Potti, D. Harpole, J. Lancaster, et al. “Oncogenic pathway signatures in human cancers as a guide to targeted therapies.” In Cancer Epidemiology Biomarkers & Prevention, 14:2743S-2743S. AMER ASSOC CANCER RESEARCH, 2005.
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    • Rich, J., C. Hans, B. Jones, R. McLendon, B. Rasheed, A. Dobra, H. Dressman, D. Bigner, J. Nevins, and M. West. “Gene expression profiling links invasion-related genes to poor survival in older glioblastoma patients.” In Neuro Oncology, 7:293–293. DUKE UNIV PRESS, 2005.
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    • Petersen, R. P., A. Bild, H. Dressman, M. B. M. Joshi, D. H. Conlon, M. West, J. R. Nevins, and D. H. Harpole. “Gene expression signatures for prognosis in NSCLC, coupled with signatures of oncogenic pathway deregulation, provide a novel approach for selection of molecular targets.” In Journal of Clinical Oncology, 23:626S-626S. AMER SOC CLINICAL ONCOLOGY, 2005.
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    • Rich, J. N., C. Hans, B. Jones, R. E. McLendon, A. Rasheed, A. Dobra, H. K. Dressman, D. D. Bigner, J. R. Nevins, and M. West. “Bayesian analysis of gene expression profiles links invasion related genes to poor survival in older glioblastoma patients.” In Proceedings of the American Association for Cancer Research, 2005:212–212, 2005.
    • Berchuck, A., E. Iversen, J. M. Lancaster, A. Henriott, H. Dressman, M. West, J. R. Nevins, and J. R. Marks. “Prediction of long-term versus short-term survival in advanced stage serous ovarian cancer using expression microarrays.” In Journal of the Society for Gynecologic Investigation, 11:182A-182A. ELSEVIER SCIENCE INC, 2004.
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    • Pittman, J. L., C. L. Tebbit, E. P. Black, H. K. Dressman, E. S. Huang, J. A. Olson, J. R. Marks, et al. “Predictive models that combine multiple forms of genomic and clinical data to achieve personalized prediction of outcomes in breast cancer.” In Breast Cancer Research and Treatment, 88:S21–22. SPRINGER, 2004.
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    • Seo, D., R. Karra, T. Wang, H. Dressman, M. West, J. Nevins, and P. Goldschmidt. “Genomic convergence in the study of human and mouse atherosclerosis.” In Circulation, 108:282–282. LIPPINCOTT WILLIAMS & WILKINS, 2003.
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    • Ferreira, M. A. R., Z. Bi, M. West, H. K. H. Lee, and D. M. Higdon. “Multiscale modelling of 1-D permeability fields.” In 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. Oxford University Press, 2003.
    • West, M. “Bayesian factor regression models in the "Large p, Small n" paradigm.” In Bayesian Statistics 7, edited by J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, and A. F. M. Smith, 733–42. CLARENDON PRESS, 2003.
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    • West, M. “Case Studies in Bayesian Statistics V.” edited by C. A. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West. Springer-Verlag, New York, 2001.
    • Aguilar, O., G. Huerta, R. Prado, and M. West. “Bayesian inference on latent structure in time series.” In Bayesian Statistics 6, edited by J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, 3–26. OXFORD UNIV PRESS, 1999.
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    • Aguilar, O., and M. West. “Analysis of hospital quality monitors using hierarchical time series models.” In Case Studies in Bayesian Statistics, Vol. 4, edited by C. A. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West, 287–302. Springer Verlag, New York, 1999.
    • Paddock, S., 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. A. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West, 339–54. Springer-Verlag, New York, 1998.
    • West, M. “Case Studies in Bayesian Statistics IV.” edited by C. A. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West. Springer-Verlag, New York, 1998.
    • West, M. “Some statistical issues in Palæoclimatology (with discussion).” In Bayesian Statistics 5, edited by J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, 461–86. Oxford University Press, 1996.
    • West, M. “Bayesian time series: Models and computations for the analysis of time series in the physical sciences.” In Maximum Entropy and Bayesian Methods, edited by K. M. Hanson and R. N. Silver, 79:23–34. KLUWER ACADEMIC PUBL, 1996.
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    • West, Mike. “Modelling and robustness issues in Bayesian time series analysis,” 231–52. Institute of Mathematical Statistics, 1996. https://doi.org/10.1214/lnms/1215453070.
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    • West, M. “Discovery sampling and selection models.” In Statistical Decision Theory and Related Topics, edited by S. S. Gupta and J. O. Berger, 221–35. Springer-Verlag, New York, 1994.
    • West, M., and G. Cao. “Assessing mechanisms of neural synaptic activity.” In Case Studies in Bayesian Statistics, Vol. 1, edited by C. A. Gatsonis, J. Hodges, R. E. Kass, and N. D. Singpurwalla, 416–28. Springer-Verlag, New York, 1993.
• Teaching & Mentoring
• 

  Recent Courses

  • STA 942S: Time Series and Forecasting 2022
  • STA 993: Independent Study 2022
  • STA 642: Time Series and Dynamic Models 2021
  • STA 701S: Readings in Statistical Science 2021
  • STA 831: Probability and Statistical Models 2021
  • STA 995: Internship 2021
  • STA 642: Time Series and Dynamic Models 2020
  • STA 693: Research Independent Study 2020
  • STA 790-1: Special Topics in Statistics 2020

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