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Fitting a fractional multinomial logit model by quasi maximum likelihood
fmlogit depvars [weight] [if] [in] [, etavar(varlist) cluster(clustervar)
constraints(numlist|matname)} level(#) nolog maximize_options ]
by ... : may be used with betafit; see help by.
fweights, and pweights are allowed; see help weights.
Description
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).
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.
Also note that fmlogit always implies the robust option because the model is fitted using quasi maximum
likelihood.
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