{smcl}
{* 05Jan2008/30dec2006/06sep2006/03aug2006}{...}
{hline}
help for {hi:fmlogit}
{hline}

{title:Fitting a fractional multinomial logit model by quasi maximum likelihood}

{p 8 17 2}
{cmd:fmlogit} 
{it:depvars} 
{weight} 
{ifin}
[{cmd:,} 
{cmdab:eta:var(}{it:varlist}{cmd:)} 
{cmdab:cl:uster(}{it:clustervar}{cmd:)} 
{cmdab:c:onstraints(}{it:numlist}|{it:matname}{cmd:})}
{cmdab:l:evel(}{it:#}{cmd:)} 
{cmd:nolog}
{it:maximize_options} 
]

{p 4 4 2}{cmd:by} {it:...} {cmd::} may be used with {cmd:betafit}; see help
{help by}. 

{p 4 4 2}{cmd:fweight}s, and {cmd:pweight}s are allowed; see help {help weights}.


{title:Description}

{p 4 4 2} 
{cmd:fmlogit} fits by quasi maximum likelihood a fractional multinomial logit
model. Each variable in depvarlist ranges between 0 and 1 and all variables in 
depvarlist must, for each observation, add up to 1: for example, they may be
proportions. It is a multivariate generalization of the fractional logit model
proposed by Papke and Wooldridge (1996). 

{p 4 4 2}
Note that cases will be ignored if the one or more of the dependent variables 
has a value less zero or more than one or if the dependent variables don't add 
up to one.

{p 4 4 2}
Also note that {cmd:fmlogit} always implies the {cmd:robust} option because 
the model is fitted using quasi maximum likelihood.


{title:Options}

{p 4 8 2}{cmd:etavar()} specifies the explanatory variables. (The name of this 
option originates from the symbol commonly used for the linear predictor, the
Greek letter eta.)

{p 4 8 2}{cmd:cluster(}{it:clustervar}{cmd:)} specifies that the observations
are independent across groups (clusters) but not necessarily within groups.
{it:clustervar} specifies to which group each observation belongs; e.g.,
{cmd:cluster(personid)} in data with repeated observations on individuals.  See
{hi:[U] 23.14 Obtaining robust variance estimates}.  

{p 4 8 2} {cmdab:c:onstraints(}{it:numlist}|{it:matname}{cmd:})} specifies
linear constraint(s) that are to be applied to the model; see help 
{help constraint}.

{p 4 8 2}{cmd:level(}{it:#}{cmd:)} specifies the confidence level, in percent,
for the confidence intervals of the coefficients; see help {help level}.

{p 4 8 2}{cmd:nolog} suppresses the iteration log.

{p 4 8 2}{it:maximize_options} control the maximization process; see 
help {help maximize}. If you are seeing many "(not concave)" messages in the 
log, using the {cmd:difficult} option may help convergence.

       
{title:Example}

{cmd}
    use http://fmwww.bc.edu/repec/bocode/c/citybudget.dta, clear

    fmlogit governing safety education recreation social urbanplanning, ///
        eta(minorityleft noleft houseval popdens)

    dfmlogit, at(minorityleft 0 noleft 0 )
{txt}
{p 4 4 2}({stata "fmlogit_ex":click to run}){p_end}


{title:Author}

{p 4 4 2}Maarten L. Buis, Universitaet Tuebingen{break}maarten.buis@uni-tuegingen.de


{title:References}

{p 4 4 2}
Papke, Leslie E. and Jeffrey M. Wooldridge. 1996.
Econometric Methods for Fractional Response Variables with an Application to 
401(k) Plan Participation Rates. {it:Journal of Applied Econometrics} 11(6):619{c -}632.


{title:Also see}

{p 4 13 2}
Online: help for {help fmlogit postestimation}, 

{p 4 13 2}
If installed: {help dirifit}