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Learn about Bayesian analysis and see examples of Bayesian features, including Bayesian econometrics, Bayesian model averaging (BMA), and Bayesian variable selection New.

See what's new in Bayesian analysis.

Also see an Overview example.

Estimation Updated

• Thousands of built-in models, by combining
  • over 60 likelihood models, including univariate and multivariate normal, asymmetric Laplace New, logit, probit, ordered logit, ordered probit, Poisson ...
  • Many prior distributions, including normal, lognormal, multivariate normal, gamma, beta, Wishart ... Updated
  • Continuous, binary, ordinal, count, and survival outcomes
  • Univariate, multivariate, and multiple-equation models
  • Linear and nonlinear models
  • Continuous univariate, multivariate, and discrete priors
• bayes: prefix Updated
  • Simply type bayes: in front of any of over 60 estimation commands to fit Bayesian regression models
  • Change any of the default priors
  • Change any of the simulation or sampling settings
  • Time-series operators
  • Control Panel lets you specify and fit models from an easy-to-use interface
• Variable selection New
• Multiple chains
• Use GUI to fit models
• Use command language to fit models
• Time-series operators

Classes of models

• Linear regression
• Nonlinear regression
• Multivariate regression
• Multivariate nonlinear regression
• Generalized linear models
• Generalized nonlinear models with canonical links
• Quantile regression New
• Zero-inflated models
• Sample-selection models
• Survival models
• Panel-data models
• Multilevel models
• Autoregressive models
• Threshold autoregressive models (TAR)
• Multivariate time-series models
• Multiple-equation models
• Lasso
• Econometrics models

Likelihood models

• Normal
• Student's t
• Lognormal
• Exponential
• Asymmetric Laplace (quantile) regression New
• Probit
• Logit/Logistic
• Binomial
• Ordered probit
• Ordered logistic
• Poisson
• Negative binomial
• Survival models
• Panel-data models
• Multilevel
• Normal
• Probit, logit/logistic, complementary log-log
• Ordered probit and logit
• Poisson and negative binomial
• Generalized linear models
• Survival
• Multivariate normal (MVN)
• Multivariate VAR
• Linear and nonlinear DSGE models
• User-defined Updated

Prior distributions

• Normal
• Generalized (location-scale) t
• Lognormal
• Uniform
• Gamma
• Inverse gamma
• Exponential
• Laplace
• Cauchy
• Half-Cauchy New
• Beta
• Chi-squared
• Rayleigh New
• Pareto
• Multivariate normal
• Dirichlet
• Wishart
• Inverse Wishart
• Bernoulli
• Geometric
• Discrete
• Poisson
• User-defined density
• User-defined log density
• Specialized priors
• MVN with exchangeable, independent, identity, and scaled covariances
• Flat
• Jeffreys
• Multivariate Jeffreys
• Zellner's g

Add your own models Updated

• Write your own programs to calculate likelihood function and choose built-in priors
• Write your own programs to calculate posterior density directly
• Use built-in adaptive MH sampling to simulate marginal posterior

Markov chain Monte Carlo (MCMC) methods

• Adaptive Metropolis-Hastings (MH)
• Hybrid MH (adaptive MH with Gibbs updates)
• Full Gibbs sampling for some models Updated
• Efficient sampling of random effects New
• Bayesian predictions New

Simulation

• Produce multiple chains
• Three MCMC methods
• Control burn-in iterations
• Control MCMC iterations
• Thinning
• Review model summary before simulation
• Save simulation results for future use

Adaptive MH sampling

• Blocking of parameters
• Adaptation within each block
• Diminishing adaptation
• Random-effects parameters
• Control scale and covariance of the proposal distribution
• Control adaptation
• Length of adaptation
• Maximum and minimum numbers of adaptive iterations
• Acceptance rate
• Adaptation rate
• Target acceptance rate
• Acceptance rate tolerance

Starting values

• Automatic
• May specify for some or all parameters
• May specify for some or all chains

Postestimation Selector

• View and run all postestimation features for your command
• Automatically updated as estimation commands are run