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Using the BACC Software for Bayesian Inference

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  • William McCausland

    (University of Minnesota)

Abstract

The BACC software provides its users with tools for Bayesian Analysis, Computation, and Communications. A new version of the software, described here, implements these tools as extensions to popular mathematical applications such as GAUSS or MATLAB. The user has available, within the application, special-purpose commands for posterior simulation and related tasks alongside familiar built-in commands for matrix computation, graphics, program flow control, and I/O. Examples illustrate the use of the software within GAUSS. Several models are currently available, including a normal linear model. Developers can extend the software by specifying new models.

Suggested Citation

  • William McCausland, 1999. "Using the BACC Software for Bayesian Inference," Computing in Economics and Finance 1999 833, Society for Computational Economics.
    • Handle: RePEc:sce:scecf9:833
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    Cited by:

    1. Takashi Kano & James M. Nason, 2014. "Business Cycle Implications of Internal Consumption Habit for New Keynesian Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(2-3), pages 519-544, March.
    2. Bryant, Henry L. & Davis, George C., 2001. "Beyond The Model Specification Problem: Model And Parameter Averaging Using Bayesian Techniques," 2001 Annual meeting, August 5-8, Chicago, IL 20689, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Kano, Takashi & 加納, 隆 & Nason, James M., 2012. "Appendix: Business Cycle Implications of Internal Consumption Habit for New Keynesian Models," Discussion Papers 2012-08, Graduate School of Economics, Hitotsubashi University.
    4. McCausland, William J., 2007. "Time reversibility of stationary regular finite-state Markov chains," Journal of Econometrics, Elsevier, vol. 136(1), pages 303-318, January.

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