you could do something where the distibutions are stochastically
independent but parametrically dependent. then you merely multiply the
densities to get the joint density, but you have to estimate them together
becasue fo the shared parameters.
oh, and nothing is beyond the scope of this class!, but there is a
question as to whether the setup would make a difference in your
situation.
Gary
On Sun, 27 Apr 2003, Kosuke Imai wrote:
This could be done if you model it hierarchically (you
also need a
variable that belongs to one equation but not to the other). But, it may
be beyond what we learned in the class... You can still model the two
decisions independently, though.
Kosuke
On Sun, 27 Apr 2003, Olivia Lau wrote:
Dear all,
Does anyone know of a paper that deals with a multiple equation
model with two different distributions? I think I have a case
where I have stochastically dependent Ys (probability of crisis,
length of crisis). The problem is that the first Y (pr crisis)
is logisitic and the second is weibull.
Any suggestions?
Thanks,
Olivia
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