{smcl}
{* 19jun2003}{...}
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help for {hi:sneop}{right:Mark Stewart (19 June 2003)}
{hline}

{title:Semi-nonparametric estimation of extended ordered probit model}

{p 4 12}{cmd:sneop} {it:depvar} [{it:varlist}] [{cmd:if} {it:exp}] [{cmd:in} {it:range}] [{cmd:weight}] 
	[{cmd:,} {cmdab:order(}{it:#}{cmd:)} {cmdab:r:obust} {cmdab:f:rom(}{it:matname}{cmd:)} ]

{p}{cmd:sneop} shares the features of all estimation commands; see help
{help est}.


{title:Description}

{p}{cmd:sneop} estimates a generalized ordered response model that nests the 
ordered probit using the semi-nonparametric estimator of Gallant and Nychka (1987). 
The unknown distribution of the stochastic error term in the underlying latent 
variable model is approximated using a Hermite series expansion.


{title:Options}

{p 0 4}{cmd:order(}{it:#}{cmd:)} specifies the order of the Hermite polynomial to be used.
The default is 3. Orders 1 and 2 give models equivalent to the Ordered Probit.

{p 0 4}{cmd:robust} specifies that the Huber/White/sandwich estimator of
variance is to be used in place of the traditional calculation; see
{hi:[U] 23.11 Obtaining robust variance estimates}.

{p 0 4}{cmd:from(}{it:matname}{cmd:)} specifies a matrix containing starting values.
This option can be used to investigate whether global maximum found.
The default uses the ordered probit estimates as starting values.


{title:Remarks}

For fuller details of the estimator and an illustration, see Stewart (2003).


{title:Examples}

{p 8 12}{inp:. sneop ordvar x1 x2 x3 x4, order(4) }

which will estimate the extended model equivalent to:

{p 8 12}{inp:. oprobit ordvar x1 x2 x3 x4 }

To use lower order model to provide starting values:

{p 8 12}{inp:. sneop ordvar x1 x2 x3 x4, order(3) }

{p 8 12}{inp:. mat start = e(b) }

{p 8 12}{inp:. sneop ordvar x1 x2 x3 x4, order(4) from(start) }


{title:Author}

{p 4 4}Mark Stewart, Economics Department, University of Warwick, U.K.{break}
<Mark.Stewart@warwick.ac.uk>


{title:References}

{p 4 8} Gallant, A.R. and D.W. Nychka (1987), "Semi-nonparametric maximum likelihood estimation",
{it:Econometrica}, 55, 363-390.

{p 4 8} Stewart, M.B. (2003), "Semi-nonparametric estimation of extended ordered probit models",
mimeo, University of Warwick.

 
{title:Also see}

{p 1 14}Manual:  {hi:[U] 23 Estimation and post-estimation commands},{p_end}
{p 10 14}{hi:[U] 29 Overview of model estimation in Stata},{p_end}
	  {hi:[R] oprobit}

{p 0 19}On-line:  help for {help est}, {help ml}, {help oprobit}.{p_end}
