intreg.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}
{* 08mar2005}{...}
{cmd:help intreg}{right:dialog:  {bf:{dialog intreg}}{space 15}}
{right:also see:  {help intreg postestimation}}
{hline}

{title:Title}

{p2colset 5 19 21 2}{...}
{p2col :{hi:[R] intreg} {hline 2}}Interval regression{p_end}


{title:Syntax}

{p 8 15 2}
{cmd:intreg}
{it:{help depvar:depvar1}}
{it:depvar2}
[{indepvars}]
{ifin}
{weight}
[{cmd:,} {it:options}]

{synoptset 31 tabbed}{...}
{synopthdr}
{synoptline}
{syntab :Model}
{synopt :{opt nocon:stant}}suppress constant term{p_end}
{synopt :{cmdab:h:et(}{varlist} [{cmd:,} {opt nocons:tant}]{cmd:)}}independent
variables to model the variance; use {opt noconstant} to suppress constant
term{p_end}
{synopt :{opth off:set(varname)}}include {it:varname} 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}

{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}}synonym for {cmd:vce(robust)}{p_end}
{synopt :{opth cl:uster(varname)}}adjust standard error for intragroup
correlation {it:varname}{p_end}

{syntab :Reporting}
{synopt :{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}
{p_end}

{syntab :Max options}
{synopt :{it:{help intreg##maximize_options:maximize_options}}}control the maximization process; seldom
used{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}
{it:depvar1}, {it:depvar2}, {it:indepvars}, and {it:varlist} may contain
time-series operators; see {help tsvarlist}.{p_end}
{p 4 6 2}
{opt bootstrap}, {opt by}, {opt jackknife}, {opt rolling}, {opt statsby},
{opt stepwise}, {opt svy}, and {opt xi} are allowed; see {help prefix}.{p_end}
{p 4 6 2}
{opt aweight}s, {opt fweight}s, {opt iweight}s, and {opt pweight}s are
allowed; see {help weight}.{p_end}
{p 4 6 2}
See {help intreg postestimation} for features available after estimation.{p_end}


{title:Description}

{pstd}
{cmd:intreg} fits a model of
y=[{it:{help depvar:depvar1}}, {it:depvar2}] on
{indepvars}, where y for each observation is either point data,
interval data, left-censored data, or right-censored data.

{pstd}
{it:depvar1} and {it:depvar2} should have the following form:

             type of data {space 16} {it:depvar1}  {it:depvar2}
             {hline 46}
             point data{space 10}{it:a} = [{it:a},{it:a}]{space 4}{it:a}{space 8}{it:a} 
             interval data{space 11}[{it:a},{it:b}]{space 4}{it:a}{space 8}{it:b}
             left-censored data{space 3}(-inf,{it:b}]{space 4}{cmd:.}{space 8}{it:b}
             right-censored data{space 3}[{it:a},inf){space 4}{it:a}{space 8}{cmd:.} 
             {hline 46}


{title:Options}

{dlgtab:Main}

{phang}
{opt noconstant}; see {help estimation options}.

{phang}
{cmd:het(}{varlist}[{opt , noconstant}]{cmd:)} specifies that
{it:varlist} be included in the specification of the conditional
variance.  This {it:varlist} enters the variance specification collectively as
multiplicative heteroskedasticity. 

{phang}
{opth offset(varname)}, {opt constraints(constraints)};
see {help estimation options}.

{dlgtab:SE/Robust}

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

{phang}
{opt robust}, {opth cluster(varname)}; see {help estimation options}.
{opt cluster()} can be used with {opt pweight}s to produce estimates for
unstratified cluster-sampled data, but see {helpb "svy:intreg"} for a command
especially designed for survey data.

{dlgtab:Reporting}

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

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

{phang}
{it:maximize_options}:
{opt dif:ficult},
{opt tech:nique(algorithm_spec)},
{opt iter:ate(#)},
[{cmd:{ul:no}}]{opt lo:g},
{opt tr:ace},
{opt hess:ian},
{opt grad:ient},
{opt showstep},
{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:Examples}

{pstd}
Assume that a dataset contains income, truncated and in categories.  Some of
the observations on income are

	   y1       y2
{p 9 27 2}20000{space 4}24000 {space 2} meaning  20000{space 2}<= income <= 24000{p_end}
{p 8 27 2}100000{space 6}. {space 4} meaning 100000 <= income

{pstd}
The command to estimate with these data is

{phang2}{cmd:. intreg y x1 x2 x3 x4}


{title:Also see}

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

{psee}
Online:  {help intreg postestimation};{break}
{helpb cnreg},
{helpb constraint},
{helpb heckman},
{helpb oprobit},
{helpb regress},
{helpb _robust},
{helpb "svy:intreg"}, 
{helpb tobit},
{helpb xtintreg},
{helpb xttobit}
{p_end}