Hello,
I am pretty new to mlogit, and still trying to figure out what models to use.I
have a data set of N individuals, each of which faces I alternatives. The
utility function of individual n, for choice i is:
u(i,n) = alpha(i) * x1(i,n) + beta * x2(i,n)
where alpha(i) is the individual specific parameter, and beta is shared among
all individuals. I don't really know how to set this up in mlogit.
If I assumed that beta is individual-specific (beta(i)), then I can divide the
data set to many subsets, each of which corresponds to a particular individual
i, and run this model for each subset to estimate alpha(i) and beta(i).
y ~ x1 + x2
This can be done just fine.
I have gone over tutorials by Train and by Heshner but I haven't found out how
to solve this problem yet. Any suggestions are welcome. Thank you so much for
your time!
[[alternative HTML version deleted]]
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
