Home  /  Products  /  Features  /  Bayesian estimation

Bayesian estimation in Stata is similar to standard estimation—simply prefix the estimation command with bayes: (see [BAYES] bayes). You can also refer to [BAYES] bayesmh and [BAYES] bayesmh evaluators for fitting more general Bayesian models.

The following estimation commands support the bayes prefix:


Linear regression models

regressLinear regressionbayes: regressExample 1, Example 2, Example 3
qreg StataNowQuantile regressionbayes: qreg
hetregressHeteroskedastic linear regressionbayes: hetregress
tobitTobit regressionbayes: tobit
intregInterval regressionbayes: intreg
truncregTruncated regressionbayes: truncreg
mvregMultivariate regressionbayes: mvreg

Binary-response regression models

logisticLogistic regression, reporting odds ratiosbayes: logistic
logitLogistic regression, reporting coefficientsbayes: logitExample
probitProbit regressionbayes: probit
cloglogComplementary log-log regressionbayes: cloglog
hetprobitHeteroskedastic probit regressionbayes: hetprobit
binregGLM for the binomial familybayes: binreg
biprobitBivariate probit regressionbayes: biprobit

Ordinal-response regression models

ologitOrdered logistic regressionbayes: ologit
oprobitOrdered probit regressionbayes: oprobit
hetoprobitHeteroskedastic ordered probit regressionbayes: hetoprobit
ziologitZero-inflated ordered logistic regressionbayes: ziologit
zioprobitZero-inflated ordered probit regressionbayes: zioprobit

Categorical-response regression models

mlogitMultinomial (polytomous) logistic regressionbayes: mlogitExample
mprobitMultinomial probit regressionbayes: mprobit
clogitConditional logistic regressionbayes: clogit

Count-response regression models

poissonPoisson regressionbayes: poisson
nbregNegative binomial regressionbayes: nbreg
gnbregGeneralized negative binomial regressionbayes: gnbreg
tpoissonTruncated Poisson regressionbayes: tpoissonExample
tnbregTruncated negative binomial regressionbayes: tnbreg
zipZero-inflated Poisson regressionbayes: zip
zinbZero-inflated negative binomial regressionbayes: zinbExample

Generalized linear models

Zero-inflated regression models

ziologitZero-inflated ordered logistic regressionbayes: ziologit
zioprobitZero-inflated ordered probit regressionbayes: zioprobit
zipZero-inflated Poisson regressionbayes: zip
zinbZero-inflated negative binomial regressionbayes: zinbExample

Fractional-response regression models

fracregFractional response regressionbayes: fracreg
betaregBeta regressionbayes: betareg

Survival regression models

Sample-selection regression models

heckmanHeckman selection modelbayes: heckmanExample
heckprobitProbit model with sample selectionbayes: heckprobit
heckoprobitOrdered probit model with sample selectionbayes: heckoprobit

Longitudinal/panel-data regression models

xtregPanel-data linear regressionbayes: xtregExample
xtlogitPanel-data logit regressionbayes: xtlogit
xtprobitPanel-data probit regressionbayes: xtprobit
xtologitPanel-data ordered logit regressionbayes: xtologitExample
xtoprobitPanel-data ordered probit regressionbayes: xtoprobit
xtmlogitPanel-data multinomial logit regressionbayes: xtmlogit
xtpoissonPanel-data Poisson regressionbayes: xtpoisson
xtnbregPanel-data negative binomial regressionbayes: xtnbreg

Multilevel regression models

mixedMultilevel linear regressionbayes: mixedExample
metobitMultilevel tobit regressionbayes: metobit
meintregMultilevel interval regressionbayes: meintreg
melogitMultilevel logistic regressionbayes: melogit
meprobitMultilevel probit regressionbayes: meprobit
mecloglogMultilevel complementary log-log regressionbayes: mecloglog
meologitMultilevel ordered logistic regressionbayes: meologit
meoprobitMultilevel ordered probit regressionbayes: meoprobit
mepoissonMultilevel Poisson regressionbayes: mepoisson
menbregMultilevel negative binomial regressionbayes: menbreg
meglmMultilevel generalized linear modelbayes: meglmExample
mestregMultilevel parametric survival regressionbayes: mestreg

Time-series models

DSGE models