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Aguilar, O., West, M. (2000). Bayesian dynamic factor models and portfolio allocation. Journal of Business and Economic Statistics, 18, 338–357.
Ahelegbey, D. F., Billio, M., Casarin, R. (2016a). Bayesian graphical models for structural vector autoregressive processes. Journal of Applied Econometrics, 31, 357–386.
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- Berry, L. R., West, M. (2019). Bayesian forecasting of many count-valued time series. Journal of Business and Economic Statistics, https://doi.org/10.1080/07350015.2019.1604372 .
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Bianchi, D., Billio, M., Casarin, R., Guidolin, M. (2019). Modeling systemic risk with Markov switching graphical SUR models. Journal of Econometrics, 210, 58–74.
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- Carvalho, C. M., Lopes, H. F., Aguilar, O. (2011). Dynamic stock selection strategies: A structured factor model framework (with discussion). In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West (Eds.), Bayesian statistics, Vol. 9, pp. 69–90. Oxford: Oxford University Press.
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Carvalho, C. M., Massam, H., West, M. (2007). Simulation of hyper-inverse Wishart distributions in graphical models. Biometrika, 94, 647–659.
- Carvalho, C. M., West, M. (2007a). Dynamic matrix-variate graphical models. Bayesian Analysis, 2, 69–98.
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- Carvalho, C. M., West, M. (2007b). Dynamic matrix-variate graphical models-A synopsis. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West (Eds.), Bayesian statistics, Vol. 8, pp. 585–590. Oxford: Oxford University Press.
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Chen, C. W. S., Lee, S. (2017). Bayesian causality test for integer-valued time series models with applications to climate and crime data. Journal of the Royal of Statistical Society (Series C: Applied Statistics), 66, 797–814.
Chen, X., Banks, D., West, M. (2019). Bayesian dynamic modeling and monitoring of network flows. Network Science, 7, 292–318.
Chen, X., Irie, K., Banks, D., Haslinger, R., Thomas, J., West, M. (2018). Scalable Bayesian modeling, monitoring and analysis of dynamic network flow data. Journal of the American Statistical Association, 113, 519–533.
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- Ferreira, M. A. R., West, M., Lee, H., Higdon, D. M. (2006). Multiscale and hidden resolution time series models. Bayesian Analysis, 2, 294–314.
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- Gruber, L. F., West, M. (2016). GPU-accelerated Bayesian learning in simultaneous graphical dynamic linear models. Bayesian Analysis, 11, 125–149.
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Gruber, L. F., West, M. (2017). Bayesian forecasting and scalable multivariate volatility analysis using simultaneous graphical dynamic linear models. Econometrics and Statistics, 3, 3–22.
- Hans, C., Dobra, A., West, M. (2007a). Shotgun stochastic search in regression with many predictors. Journal of the American Statistical Association, 102, 507–516.
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- Hans, C., Wang, Q., Dobra, A., West, M. (2007b). SSS: High-dimensional Bayesian regression model search. Bulletin of the International Society for Bayesian Analysis, 24, 8–9.
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- Irie, K., West, M. (2019). Bayesian emulation for multi-step optimization in decision problems. Bayesian Analysis, 14, 137–160.
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- Jones, B., Dobra, A., Carvalho, C. M., Hans, C., Carter, C., West, M. (2005). Experiments in stochastic computation for high-dimensional graphical models. Statistical Science, 20, 388–400.
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Jones, B., West, M. (2005). Covariance decomposition in undirected Gaussian graphical models. Biometrika, 92, 779–786.
Kastner, G., Frühwirth-Schnatter, S., Lopes, H. F. (2017). Efficient Bayesian inference for multivariate factor stochastic volatility models. Journal of Computational and Graphical Statistics, 26, 905–917.
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Kliesen, K. L., Smith, D. C. (2010). Measuring financial market stress: The St. Louis Fed’s financial stress index (STLFSI). In Federal Reserve Bank of St Louis National Economic Trends.
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Koop, G., Korobilis, D. (2010). Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics, 3, 267–358.
Koop, G., Korobilis, D. (2013). Large time-varying parameter VARs. Journal of Econometrics, 177, 185–198.
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- Liu, F., West, M. (2009). A dynamic modelling strategy for Bayesian computer model emulation. Bayesian Analysis, 4, 393–412.
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- Lopes, H. F., Carvalho, C. M. (2007). Factor stochastic volatility with time varying loadings and Markov switching regimes. Journal of Statistical Planning and Inference, 137, 3082–3091.
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McAlinn, K., Aastveit, K. A., Nakajima, J., West, M. (2019). Multivariate Bayesian predictive synthesis in macroeconomic forecasting. Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2019.1660171 .
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McAlinn, K., West, M. (2019). Dynamic Bayesian predictive synthesis in time series forecasting. Journal of Econometrics, 210, 155–169.
Nakajima, J., West, M. (2013a). Bayesian analysis of latent threshold dynamic models. Journal of Business and Economic Statistics, 31, 151–164.
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- Nakajima, J., West, M. (2015). Dynamic network signal processing using latent threshold models. Digital Signal Processing, 47, 6–15.
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- Nakajima, J., West, M. (2017). Dynamics and sparsity in latent threshold factor models: A study in multivariate EEG signal processing. Brazilian Journal of Probability and Statistics, 31, 701–731.
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Prado, R., Molina, F. J., Huerta, G. (2006). Multivariate time series modeling and classification via hierarchical VAR mixtures. Computational Statistics and Data Analysis, 51, 1445–1462.
- Prado, R., West, M. (2010). Time series: Modeling, computation and inference. Boca Raton: Chapman & Hall.
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Tebaldi, C., West, M., Karr, A. F. (2002). Statistical analyses of freeway traffic flows. Journal of Forecasting, 21, 39–68.
Terui, N., Ban, M. (2014). Multivariate time series model with hierarchical structure for over-dispersed discrete outcomes. Journal of Forecasting, 33, 379–390.
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Wang, H. (2010). Sparse seemingly unrelated regression modelling: Applications in econometrics and finance. Computational Statistics and Data Analysis, 54, 2866–2877.
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Wang, H., West, M. (2009). Bayesian analysis of matrix normal graphical models. Biometrika, 96, 821–834.
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Yelland, P. M. (2009). Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management. International Journal of Production Economics, 118, 95–103.
Zhao, Z. Y., Xie, M., West, M. (2016). Dynamic dependence networks: Financial time series forecasting and portfolio decisions. Applied Stochastic Models in Business and Industry, 32, 311–339, (with discussion).
Zhou, X., Nakajima, J., West, M. (2014). Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models. International Journal of Forecasting, 30, 963–980.