help fmm postestimation                                         also see:  fmm 
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Title

fmm postestimation -- Postestimation tools for fmm


Description

    The following postestimation commands are available for fmm:

    command      description
    -------------------------------------------------------------------------
INCLUDE help post_estat
INCLUDE help post_estimates
INCLUDE help post_lincom
INCLUDE help post_lrtest
INCLUDE help post_margins
INCLUDE help post_nlcom
    predict      predictions including component probabilities
INCLUDE help post_test
INCLUDE help post_testnl
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Syntax for predict

        predict [type] newvar [if] [in] [, statistic equation(component#)]

    statistic    Description
    -------------------------------------------------------------------------
    Main
      mean       predicted mean; the default
      prior      prior component probability
      posterior  posterior component probability
    -------------------------------------------------------------------------
    Option equation(component#) is required for prior and posterior.  It is
      also required for mean if predicted within-component means are desired.

INCLUDE help esample


Options for predict

    mean, the default, calculates the predicted mean.

        To obtain within component means, specify the equation(component#)
        option.

    prior calculates the prior component probabilities.  With prior,
        equation(component#) must also be specified.

    posterior calculates the posterior component probabilities.  With
        posterior, equation(component#) must also be specified.


Marginal effects

    Marginal effects can be calculated separately for the overall conditional
    mean as well as for within-component means, prior and posterior
    probabilities.  To calculate marginal effects for within-component means,
    prior and posterior probabilities, run margins separately for each
    component, as shown in the examples below. Note that fmm has not been
    updated to accommodate factor variables.


Examples

    Mixture of normals

    . webuse womenwk, clear

    . fmm wagefull educ age married, mix(normal) comp(2)

    . predict wfhat

    . predict wfhat1, eq(component1)

    . predict wfhat2, eq(component2)

    . predict wfhatpri, prior eq(component1)

    . predict wfhatpos, posterior eq(component1)

    . sum wagefull wfhat*

    . drop wfhat*


    Mixture of Negative Binomials (Type 2)

    . webuse medpar, clear

    . gen los0 = los - 1

    . fmm exlos died hmo type2-type3, mix(negbin2) comp(2) comp(2)

    . predict wfhat

    . predict l0hat1, eq(component1)

    . predict l0hat2, eq(component2)

    . predict l0hatpri, prior eq(component1)

    . predict l0hatpos, posterior eq(component1)

    . sum los0 l0hat*

    . drop l0hat*

    . margins, dydx(*) predict(eq(component1))

    . margins, dydx(*) predict(eq(component2))

    . margins, dydx(*)


Also see

    fmm; estimates, lincom, lrtest, margins, nlcom, predictnl, suest, test, 
             testnl