367
Views
3
CrossRef citations to date
0
Altmetric
Original Articles

Bayesian Dynamic Dirichlet Models

&
Pages 787-818 | Received 14 Nov 2012, Accepted 08 Apr 2013, Published online: 10 Sep 2014

References

  • Aitchison, J. (1982). The statistical analysis of compositional data. Journal of the Royal Statistical Society: Series B 44:139–177.
  • Aitchison, J. (2003). The Statistical Analysis of Compositional Data. 2nd ed. London: Chapman and Hall.
  • Aitchison, J., Shen, S.M. (1980). Logistic-normal distributions: Some properties and uses. Biometrika 67:261–272.
  • Billheimer, D., Cardoso, T., Freeman, E., Guttorp, P., Ko, H., Silkey, M. (1997). Natural variability of Benthic species composition in the Delaware Bay. Journal of Environmental and Ecological Statistics 4:95–115.
  • Blei, D.M., Lafferty, J.D. (2006). Dynamic topic models. In: Proceedings of the 23rd International Conference on Machine Learning. Pittsburgh, PA, 113–120.
  • Camargo, A.P., Stern, J.M., Lauretto, M.S. (2012). Estimation and model selection in Dirichlet regression. AIP Conf. Proc. 1443:206.
  • Carter, C.K., Kohn, R. (1994). On Gibbs sampling for state-space models. Biometrika 81:541–553.
  • Cribari-Neto, F., Zeileis, A. (2010). Beta regression in R. Journal of Statistical Software 34:1–24.
  • da-Silva, C.Q., Migon, H.S., Correia, L.T. (2011). Dynamic Bayesian beta models. Computational Statistics and Data Analysis 55:2074–2089.
  • Ferrari, S. L.P., Cribari-Neto, F. (2004). Beta regression for modeling rates and proportions. Journal of Applied Statistics 31:799–815.
  • Frühwirth-Schnatter, S. (1994). Data augmentation and dynamic linear models. Journal of Time Series Analysis 15:183–202.
  • Gamerman, D. (1998). Markov chain Monte Carlo for dynamic generalized linear models. Biometrika 85:215–227.
  • Gelman, A., Rubin, D.B. (1992). Inference from iterative simulation using multiple sequences (with discussion). Statistical Science 7:457–511.
  • Geweke, J., Tanizaki, H. (2001). Bayesian estimation of state space models using Metropolis-Hastings algorithm within Gibbs sampling. Computation Statistics and Data Analysis 37:151–170.
  • Godolphin, E.J., Triantafyllopoulos, K. (2006). Decomposition of time series models in state-space form. Computational Statistics and Data Analysis 50:2232–2246.
  • Grunwald, G.K., Raftery, A.E., Guttorp, P. (1993). Time series of continuous proportions. Journal of the Royal Statistical Society. Series B 55:103–116.
  • Hankin, R. K.S. (2010). A generalization of the Dirichlet distribution. Journal of Statistical Software 33:1–18.
  • Heidelberger, P., Welch, P. (1983). Simulation run length control in the presence of initial transient. Operations Research 31:1109–1144.
  • Hijazi, R.H. (2009). Modeling compositional data using Dirichlet regression models. Journal of Applied Probability Statistics 4:77–91.
  • Johnson, S.G., Narasimhan, B. (2009). Cubature: Adaptive multivariate integration over hypercubes. R package version 1.0.
  • Lange, K. (1999). Numerical Analysis for Statisticians. New York: Springer.
  • Lindsey, J.K., Lambert, P. (1995). Dynamic generalized linear models and repeated measurements. Journal of Statistical Planning and Inference 47:129–139.
  • Nachif, M. C.A. (2006). Homicide as a public health problem in the city of Campo Grande, Mato Grosso do Sul, Brazil. Psicologia Sociedade 18:99–104.
  • Nelder, J.A., Wedderburn, R. W.M. (1972). Generalized linear models. Journal of the Royal Statistical Society. Series A 135:370–384.
  • Pole, A., West, M., Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Boca Raton:Chapman and Hall/CRC.
  • Pruteanu-Malinici, L.R., Paisley, J., Wang, E., Carin, L. (2010). Hierarchical Bayesian modeling of topics in time-stamped documents. IEEE Transactions Pattern Analysis and Machine Intelligence 32:996–1011.
  • Quintana, J.M., West, M. (1988). Time series analysis of compositional data. In: Bernardo, J.M., DeGroot, M.H., Lindley, D.V., Smith, A. F.M., eds. Bayesian Statistics 44. pp. 747–756, New York: Oxford University Press.
  • Ravines, R., Migon, H., Schmidt, A. (2007). An efficient sampling scheme for dynamic generalized models. Technical Report 201/2007, Departamento de Métodos Estatísticos - IM- UFRJ.
  • Reichenheim, M.E., Souza, E.R., Moraes, C.L., Jorge, M. H. P. M., Silva, C. M. F. P., Minayo, M. C.S. (2011). Violence and injuries in Brazil: the effect, progress made, and challenges ahead. The Lancet 377:1962–1975.
  • Shephard, N., Pitt, M. (1997). Likelihood analysis of non-Gaussian measurement time series. Biometrika 84:653–667.
  • Smith, J.Q. (1979). A Generalization of the Bayesian steady forecasting model. Journal of the Royal Statistical Society. Series B 41:375–387.
  • Tierney, L., Kadane, J.B. (1986). Accurate approximations for the posterior moments and marginal densities. Journal of the American Statistical Association 81:82–86.
  • Wang, C., Blei, D.M., Heckerman, D. (2008). Continuous Time Dynamic Topic Models. In Proceedings of UAI. 579–586.
  • West, M., Harrison, P.J. (1997). Bayesian Forecasting and Dynamic Models.2nd ed. New York: Springer.
  • West, M., Harrison, P.J., Migon, H.S. (1985). Dynamic generalized linear models and Bayesian forecasting. Journal of the American Statistical Association 80:73–97.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.