zip.hlp

是一个经济学管理应用软件 很难找的 但是经济学学生又必须用到

{smcl}
{* 22mar2005}{...}
{cmd:help zip} {right:dialog:  {bf:{dialog zip}}{space 15}}
{right:also see:  {help zip postestimation}}
{hline}

{title:Title}

{p2colset 5 16 18 2}{...}
{p2col :{hi:[R] zip} {hline 2}}Zero-inflated Poisson regression{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 15 2}
{cmd:zip} {depvar} [{indepvars}] {ifin} {weight}{cmd:,}{break} 
   {opt inf:late}{cmd:(}{varlist}[{cmd:,} {opth off:set(varname)}]|{cmd:_cons)}
   [{it:options}]

{synoptset 28 tabbed}{...}
{synopthdr:options}
{synoptline}
{syntab:Model}
{p2coldent :* {opt inf:late()}}equation that determines whether the count is
zero{p_end}
{synopt :{opt nocon:stant}}suppress constant term{p_end}
{synopt :{opth exp:osure(varname:varname_e)}}include {opt ln(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 probit}}use probit model to characterize excess zeros;
default is logit{p_end}

{syntab:SE/Robust}
{synopt :{opth vce(vcetype)}}{it:vcetype} may be {opt oim}, {opt r:obust},
{opt opg}, {opt boot:strap}, or {opt jack:knife}{p_end}
{synopt :{opt r:obust}}compute standard errors using the robust/sandwich
estimator{p_end}
{synopt :{opth cl:uster(varname)}}adjust standard errors for intragroup
correlation{p_end}

{syntab:Reporting}
{synopt :{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}{p_end}
{synopt :{opt irr}}report incidence-rate ratios{p_end}
{synopt :{opt vuong}}report Vuong test results{p_end}

{syntab:Max options}
{synopt :{it:{help zip##maximize_options:maximize_options}}}control maximization process; seldom used{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}*{{opt inf:late}{cmd:(}{varlist}[{cmd:,} 
{opth off:set(varname)}]|{cmd:_cons)} is required.{p_end}
{p 4 6 2}{cmd:bootstrap}, {cmd:by}, {cmd:jackknife}, {cmd:rolling},
{cmd:statsby}, and {cmd:xi} are allowed; see {help prefix}.{p_end}
{p 4 6 2}{cmd:fweight}s, {cmd:iweight}s, and {cmd:pweight}s are allowed; see
{help weight}.{p_end}
{p 4 6 2}See {help zip postestimation} for additional capabilities of
estimation commands.


{title:Description}

{pstd}
{cmd:zip} estimates a zero-inflated Poisson regression of {depvar} on
{indepvars}, where {it:depvar} is a nonnegative count variable.


{title:Options}

{dlgtab:Model}

{phang}
{cmd:inflate(}{varlist}[{cmd:,} {cmd:offset(}{varname}{cmd:)}]|{cmd:_cons)}
specifies the equation that determines whether the observed count is zero.
Conceptually, omitting {opt inflate()} would be equivalent to fitting the
model with {helpb poisson}.

{pmore}
{cmd:inflate(}{varlist}[{cmd:, offset(}{varname}{cmd:)}]{cmd:)}
specifies the variables in the equation.  You may optionally include an offset
for this {varlist}.

{pmore}
{cmd:inflate(_cons)} specifies that the equation determining whether
the count is zero contains only an intercept.  To run a zero-inflated model of
{depvar} with only an intercept in both equations, type
{bind:{cmd:zip} {it:depvar}{cmd:,} {cmd:inflate(_cons)}}.

{phang}
{opt noconstant}, {opt exposure(varname_e)}, {opt offset(varname_o)}, 
{opt constraints(constraints)}; see {help estimation options}. 

{phang}
{opt probit} requests that a probit, instead of logit, model be used to
characterize the excess zeros in the data.

{dlgtab:SE/Robust}

{phang}
{opt vce(vcetype)}; see {it:{help vce_option}}.

{phang}
{opt robust}, {opth cluster(varname)}; see
 {help estimation options##robust:estimation options}.

{dlgtab:Reporting}

{phang}
{opt level(#)}; see {help estimation options##level():estimation options}. 

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

{phang}
{opt vuong} specifies that the Vuong test of ZIP versus Poisson (or ZIP versus
negative binomial) be reported.  This test statistic has a standard normal
distribution with large positive values favoring the ZIP (ZINB) model and
large negative values favoring the Poisson (negative binomial) model.

{marker maximize_options}{...}
{dlgtab:Max options}

{phang}
{it:maximize_options}: {opt dif:ficult}, {opt tech:nique(algorithm_spec)}, 
{opt iter:ate(#)}, [{cmd:{ul:no}}]{cmd:{ul:lo}}{cmd:g}, {opt tr:ace}, 
{opt grad:ient}, {opt showstep}, {opt hess:ian}, {opt shownr:tolerance},
{opt tol:erance(#)}, {opt ltol:erance(#)}, {opt gtol:erance(#)},
{opt nrtol:erance(#)}, {opt nonrtol:erance}, {opt from(init_specs)}; see
{help maximize}.  These options are seldom used.


{title:Example}

{phang}{cmd:. zip accidents DayIsMon, inflate(weekend summer) exposure(time)}


{title:Also see}

{psee}
Manual:  {bf:[R] zip}

{psee}
Online:  {help zip postestimation};{break}
{helpb constraint}, {helpb glm}, {helpb nbreg}, {helpb poisson},
{helpb xtnbreg}, {helpb zinb}, {helpb ztp}{p_end}