{smcl}
{* *! version 1.1.21  03may2011}{...}
{viewerdialog tpoisson "dialog tpoisson"}{...}
{viewerdialog "svy: tpoisson" "dialog tpoisson, message(-svy-) name(svy_tpoisson)"}{...}
{vieweralsosee "[R] tpoisson" "mansection R tpoisson"}{...}
{vieweralsosee "" "--"}{...}
{vieweralsosee "[R] tpoisson postestimation" "help tpoisson postestimation"}{...}
{vieweralsosee "" "--"}{...}
{vieweralsosee "[R] nbreg" "help nbreg"}{...}
{vieweralsosee "[R] poisson" "help poisson"}{...}
{vieweralsosee "[SVY] svy estimation" "help svy_estimation"}{...}
{vieweralsosee "[R] tnbreg" "help tnbreg"}{...}
{vieweralsosee "[XT] xtpoisson" "help xtpoisson"}{...}
{vieweralsosee "[R] zinb" "help zinb"}{...}
{vieweralsosee "[R] zip" "help zip"}{...}
{viewerjumpto "Syntax" "tpoisson##syntax"}{...}
{viewerjumpto "Description" "tpoisson##description"}{...}
{viewerjumpto "Options" "tpoisson##options"}{...}
{viewerjumpto "Examples" "tpoisson##examples"}{...}
{viewerjumpto "Saved results" "tpoisson##saved_results"}{...}
{title:Title}

{p2colset 5 21 23 2}{...}
{p2col :{manlink R tpoisson} {hline 2}}Truncated Poisson regression{p_end}
{p2colreset}{...}


{marker syntax}{...}
{title:Syntax}

{p 8 16 2}
{cmd:tpoisson} {depvar} [{indepvars}] {ifin} {weight} [{cmd:,}
{it:options}]

{synoptset 26 tabbed}{...}
{synopthdr}
{synoptline}
{syntab:Model}
{synopt :{opt nocon:stant}}suppress constant term{p_end}
{synopt:{cmd:ll(}{it:#}|{varname}{cmd:)}}truncation point;
default value is {cmd:ll(0)}, zero truncation{p_end}
{synopt :{opth e:xposure(varname:varname_e)}}include ln({it:varname_e})
in model with coefficient constrained to 1{p_end}
{synopt :{opth off:set(varname:varname_o)}}include {it:varname_o} in model with coefficient
constrained to 1{p_end}
{synopt :{cmdab:const:raints(}{it:{help estimation options##constraints():constraints}}{cmd:)}}apply specified linear constraints{p_end}
{synopt:{opt col:linear}}keep collinear variables{p_end}

{syntab:SE/Robust}
{synopt :{opth vce(vcetype)}}{it:vcetype} may be {opt oim},
  {opt r:obust}, {opt cl:uster} {it:clustvar}, {opt opg}, {opt boot:strap},
  or {opt jack:knife}{p_end}

{syntab:Reporting}
{synopt :{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}
{p_end}
{synopt :{opt ir:r}}report incidence-rate ratios{p_end}
{synopt :{opt nocnsr:eport}}do not display constraints{p_end}
{synopt :{it:{help tpoisson##display_options:display_options}}}control
INCLUDE help shortdes-displayoptall

{syntab:Maximization}
{synopt :{it:{help tpoisson##maximize_options:maximize_options}}}control the
maximization process; seldom used{p_end}

INCLUDE help shortdes-coeflegend
{synoptline}
{p2colreset}{...}
INCLUDE help fvvarlist
{p 4 6 2}{it:depvar} and {it:indepvars} may contain time-series operators;
see {help tsvarlist}.{p_end}
{p 4 6 2}{opt bootstrap}, {opt by}, {opt jackknife}, {opt rolling},
{opt statsby}, and {opt svy} are allowed; see {help prefix}.{p_end}
{p 4 6 2}Weights are not allowed with the {helpb bootstrap} prefix.{p_end}
{p 4 6 2}
{opt vce()} and weights are not allowed with the {helpb svy} prefix.
{p_end}
{p 4 6 2}{opt fweight}s, {opt iweight}s, and {opt pweight}s are allowed; see
{help weight}.{p_end}
{p 4 6 2}
{opt coeflegend} does not appear in the dialog box.{p_end}
{p 4 6 2}See {manhelp tpoisson_postestimation R:tpoisson postestimation} for
features
available after estimation.{p_end}


{title:Menu}

{phang}
{bf:Statistics > Count outcomes > Truncated Poisson regression}


{marker description}{...}
{title:Description}

{pstd}
{cmd:tpoisson} estimates the parameters of a truncated Poisson
model by maximum likelihood.  The dependent variable
{depvar} is regressed on {indepvars}, where {it:depvar} is a
positive count variable whose values are all above the
truncation point.


{marker options}{...}
{title:Options}

{dlgtab:Model}

{phang}
{opt noconstant}; see
{helpb estimation options##noconstant:[R] estimation options}.

{phang}
{cmd:ll(}{it:#}|{varname}{cmd:)} specifies the truncation point, which is
a nonnegative integer.  The default is zero truncation, {cmd:ll(0)}.

{phang}
{opth exposure:(varname:varname_e)}, {opt offset(varname_o)},
{opt constraints(constraints)}, {opt collinear}; see
{helpb estimation options:[R] estimation options}.

{dlgtab:SE/Robust}

INCLUDE help vce_asymptall

{dlgtab:Reporting}

{phang}
{opt level(#)}; see {helpb estimation options##level():[R] estimation options}.

{phang}
{opt irr} reports estimated coefficients transformed to incidence-rate
ratios, that is, exp(b) rather than b.  Standard errors and confidence
intervals are similarly transformed.  This option affects how results are
displayed, not how they are estimated.  {opt irr} may be specified at
estimation or when replaying previously estimated results.

{phang}
{opt nocnsreport}; see
     {helpb estimation options##nocnsreport:[R] estimation options}.

{marker display_options}{...}
{phang}
{it:display_options}:
{opt noomit:ted},
{opt vsquish},
{opt noempty:cells},
{opt base:levels},
{opt allbase:levels},
{opth cformat(%fmt)},
{opt pformat(%fmt)},
{opt sformat(%fmt)}, and
{opt nolstretch};
    see {helpb estimation options##display_options:[R] estimation options}.

{marker maximize_options}{...}
{dlgtab:Maximization}

{phang}
{it:maximize_options}:
{opt dif:ficult},
{opth tech:nique(maximize##algorithm_spec:algorithm_spec)},
{opt iter:ate(#)},
[{cmdab:no:}]{opt lo:g},
{opt tr:ace},
{opt grad:ient},
{opt showstep},
{opt hess:ian},
{opt showtol:erance},
{opt tol:erance(#)}, {opt ltol:erance(#)},
{opt nrtol:erance(#)}, {opt nonrtol:erance}, and
{opt from(init_specs)}; see {manhelp maximize R}.  These options are seldom
used.

{pmore}
Setting the optimization type to {cmd:technique(bhhh)} resets the default
{it:vcetype} to {cmd:vce(opg)}.

{pstd}
The following option is available with {opt tpoisson} but is not shown in the
dialog box:

{phang}
{opt coeflegend}; see
     {helpb estimation options##coeflegend:[R] estimation options}.


{marker examples}{...}
{title:Examples}

    {hline}
{pstd}Setup{p_end}
{phang2}{cmd:. webuse runshoes}{p_end}

{pstd}Truncated Poisson regression with default truncation point of 0{p_end}
{phang2}{cmd:. tpoisson shoes distance i.male age}{p_end}

    {hline}
{pstd}Setup{p_end}
{phang2}{cmd:. replace shoes = . if shoes < 4}{p_end}

{pstd}Truncated Poisson regression with truncation point of 3 and exposure
variable {cmd:age}{p_end}
{phang2}{cmd:. tpoisson shoes distance male, exposure(age) ll(3)}{p_end}

    {hline}


{marker saved_results}{...}
{title:Saved results}

{pstd}
{cmd:tpoisson} saves the following in {cmd:e()}:

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Scalars}{p_end}
{synopt:{cmd:e(N)}}number of observations{p_end}
{synopt:{cmd:e(k)}}number of parameters{p_end}
{synopt:{cmd:e(k_eq)}}number of equations in {cmd:e(b)}{p_end}
{synopt:{cmd:e(k_eq_model)}}number of equations in overall model test{p_end}
{synopt:{cmd:e(k_dv)}}number of dependent variables{p_end}
{synopt:{cmd:e(df_m)}}model degrees of freedom{p_end}
{synopt:{cmd:e(r2_p)}}pseudo-R-squared{p_end}
{synopt:{cmd:e(ll)}}log likelihood{p_end}
{synopt:{cmd:e(ll_0)}}log likelihood, constant-only model{p_end}
{synopt:{cmd:e(N_clust)}}number of clusters{p_end}
{synopt:{cmd:e(chi2)}}chi-squared{p_end}
{synopt:{cmd:e(p)}}significance{p_end}
{synopt:{cmd:e(rank)}}rank of {cmd:e(V)}{p_end}
{synopt:{cmd:e(ic)}}number of iterations{p_end}
{synopt:{cmd:e(rc)}}return code{p_end}
{synopt:{cmd:e(converged)}}{cmd:1} if converged, {cmd:0} otherwise{p_end}

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Macros}{p_end}
{synopt:{cmd:e(cmd)}}{cmd:tpoisson}{p_end}
{synopt:{cmd:e(cmdline)}}command as typed{p_end}
{synopt:{cmd:e(depvar)}}name of dependent variable{p_end}
{synopt:{cmd:e(llopt)}}contents of {cmd:ll()}, or {cmd:0} if not specified{p_end}
{synopt:{cmd:e(wtype)}}weight type{p_end}
{synopt:{cmd:e(wexp)}}weight expression{p_end}
{synopt:{cmd:e(title)}}title in estimation output{p_end}
{synopt:{cmd:e(clustvar)}}name of cluster variable{p_end}
{synopt:{cmd:e(offset)}}linear offset variable{p_end}
{synopt:{cmd:e(chi2type)}}{cmd:Wald} or {cmd:LR}; type of model chi-squared
	test{p_end}
{synopt:{cmd:e(vce)}}{it:vcetype} specified in {cmd:vce()}{p_end}
{synopt:{cmd:e(vcetype)}}title used to label Std. Err.{p_end}
{synopt:{cmd:e(opt)}}type of optimization{p_end}
{synopt:{cmd:e(which)}}{cmd:max} or {cmd:min}; whether optimizer is to perform
                         maximization or minimization{p_end}
{synopt:{cmd:e(ml_method)}}type of {cmd:ml} method{p_end}
{synopt:{cmd:e(user)}}name of likelihood-evaluator program{p_end}
{synopt:{cmd:e(technique)}}maximization technique{p_end}
{synopt:{cmd:e(properties)}}{cmd:b V}{p_end}
{synopt:{cmd:e(predict)}}program used to implement {cmd:predict}{p_end}
{synopt:{cmd:e(asbalanced)}}factor variables {cmd:fvset} as
{cmd:asbalanced}{p_end}
{synopt:{cmd:e(asobserved)}}factor variables {cmd:fvset} as
{cmd:asobserved}{p_end}

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Matrices}{p_end}
{synopt:{cmd:e(b)}}coefficient vector{p_end}
{synopt:{cmd:e(Cns)}}constraints matrix{p_end}
{synopt:{cmd:e(ilog)}}iteration log (up to 20 iterations){p_end}
{synopt:{cmd:e(gradient)}}gradient vector{p_end}
{synopt:{cmd:e(V)}}variance-covariance matrix of the estimators{p_end}
{synopt:{cmd:e(V_modelbased)}}model-based variance{p_end}

{synoptset 20 tabbed}{...}
{p2col 5 20 24 2: Functions}{p_end}
{synopt:{cmd:e(sample)}}marks estimation sample{p_end}
{p2colreset}{...}
