Stata 15 help for fmm_pointmass

[FMM] fmm: pointmass -- Finite mixtures models with a density mass at a single point

Syntax

fmm [if] [in] [weight] [, fmmopts]: (pointmass depvar [, options]) (component_1) [(component_2) ...]

component is defined in [FMM] fmm.

options Description ------------------------------------------------------------------------- lcprob(varlist) specify independent variables for class probability value(#) integer-valued location of the point mass ------------------------------------------------------------------------- depvar may contain time-series operators; see tsvarlist.

fmmopts Description ------------------------------------------------------------------------- Model lcinvariant(pclassname) specify parameters that are equal across classes; default is lcinvariant(none) lcprob(varlist) specify independent variables for class probabilities lclabel(name) name of the categorical latent variable; default is lclabel(Class) lcbase(#) base latent class constraints(constraints) apply specified linear constraints collinear keep collinear variables

SE/Robust vce(vcetype) vcetype may be oim, robust, or cluster clustvar

Reporting level(#) set confidence level; default is level(95) nocnsreport do not display constraints noheader do not display header above parameter table nodvheader do not display dependent variables information in the header notable do not display parameter table display_options control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling

Maximization maximize_options control the maximization process startvalues(svmethod) method for obtaining starting values; default is startvalues(factor) emopts(maxopts) control EM algorithm for improved starting values noestimate do not fit the model; show starting values instead

coeflegend display legend instead of statistics ------------------------------------------------------------------------- varlist may contain factor variables; see fvvarlist. by, statsby, and svy are allowed; see prefix. vce() and weights are not allowed with the svy prefix. fweights, iweights, and pweights are allowed; see weight. coeflegend does not appear in the dialog box. See [FMM] fmm postestimation for features available after estimation. For a detailed description of fmmopts, see Options in [FMM] fmm.

pclassname Description ------------------------------------------------------------------------- cons intercepts and cutpoints coef fixed coefficients errvar covariances of errors scale scaling parameters ------------------------------------------------------------------------- all all the above none none of the above; the default -------------------------------------------------------------------------

Menu

Statistics > FMM (finite mixture models) > General estimation and regression

Description

fmm: pointmass is a degenerate distribution that takes on a single integer value with probability one. This distribution cannot be used by itself and is always combined with other fmm distributions, often to model zero-inflated outcomes.

Options

lcprob(varlist) specifies that the linear prediction for belonging to the point mass component includes the variables in varlist. lcinvariant() has no effect on these parameters.

value(#) specifies the value of depvar at which the latent class has a singular point mass. The default is value(0). Only integer values are allowed for #.

Remarks

For a general introduction to finite mixture models, see [FMM] fmm intro.

Examples

--------------------------------------------------------------------------- Setup . webuse fish2

Zero-inflated Poisson model as a mixture of a point mass distribution at zero and a Poisson regression model . fmm: (pointmass count) (poisson count persons boat)

Include child and camper as predictors of membership for the point mass component . fmm: (pointmass count, lcprob(child camper)) (poisson count persons boat)

--------------------------------------------------------------------------- Setup . webuse lenses . stset t, failure(fail)

Cure model as a mixture of a point mass distribution at zero and a Weibull survival model . fmm: (pointmass fail) (streg inclength i.sex age10, distribution(weibull))

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Stored results

See Stored results in [FMM] fmm.


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