Bayesian Estimation Tools (BET)#

A suite of tools for bayesian estimation and analysis of a pre-packaged models in GAUSS.

Description#

The Bayesian Estimation Tools package provides a suite of tools for estimation and analysis of a number of pre-packaged models. The internal Bayesian models provide quickly accessible, full-stage modeling including data generation, estimation, and post-estimation analysis. Modeling flexibility is provided through control structures for setting modeling parameters.

Installation#

If you’re interested in purchasing BET Please contact us to request pricing and installation information.

If you already own BET , you can use the GAUSS Package Manager for quick download and installation..

Requires GAUSS/GAUSS Engine/GAUSS Light v13.1 or higher.

Key Features#

Data generation tools#

  • Univariate and multivariate linear models

  • Autoregressive error terms (AR)

  • Hierarchical Bayes (HB)

  • Probit and logit data

Supported models for Markov Chain Monte Carlo (MCMC) Estimation#

  • Univariate and multivariate linear models

  • Autoregressive error terms (AR)

  • Hierarchical Bayes (HB)

  • Probit model

  • Dynamic two-factor model

  • Structural vector autoregressive (SVAR)

Flexible MCMC estimation controls#

  • Number of saved iterations

  • Skipped iterations

  • Burn-in iterations

  • Total number of iterations

  • Inclusion of intercept

  • Optional graph and results output

  • Elective maximum likelihood estimation (MLE) initialization

Comprehensive results#

  • Draws for all parameters at each iteration

  • Posterior mean of parameters

  • Posterior standard deviation of parameters

  • Predicted variable values and residuals

  • Correlation matrix between observed and predicted data

  • PDF values and corresponding PDF graphs

  • Log-likelihood values (when applicable)

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