## Stata 15 help for fmm_estimation

```
[FMM] fmm estimation -- Fitting finite mixture models

Description

Finite mixture models (FMMs) are used to classify observations, to adjust
for clustering, and to model unobserved heterogeneity.  In finite mixture
modeling, the observed data are assumed to belong to several unobserved
subpopulations called classes, and mixtures of probability densities or
regression models are used to model the outcome of interest.  After
fitting the model, class membership probabilities can also be predicted
for each observation.

Linear regression models

[FMM] fmm: regress              Linear regression
[FMM] fmm: truncreg             Truncated regression
[FMM] fmm: intreg               Interval regression
[FMM] fmm: tobit                Tobit regression
[FMM] fmm: ivregress            Instrumental-variables regression

Binary-response regression models

[FMM] fmm: logit                Logistic regression, reporting
coefficients
[FMM] fmm: probit               Probit regression
[FMM] fmm: cloglog              Complementary log-log regression

Ordinal-response regression models

[FMM] fmm: ologit               Ordered logistic regression
[FMM] fmm: oprobit              Ordered probit regression

Categorical-response regression models

[FMM] fmm: mlogit               Multinomial (polytomous) logistic
regression

Count-response regression models

[FMM] fmm: poisson              Poisson regression
[FMM] fmm: nbreg                Negative binomial regression
[FMM] fmm: tpoisson             Truncated Poisson regression

Generalized linear models

[FMM] fmm: glm                  Generalized linear models

Fractional-response regression models

[FMM] fmm: betareg              Beta regression

Survival regression models

[FMM] fmm: streg                Parametric survival models

fmm: allows different regression models for different components of the
mixture; see [FMM] fmm. fmm: also allows one or more components to be a
degenerate distribution taking on a single integer value with probability
one; see [FMM] fmm: pointmass.

```