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- Newsgroups: sci.math.stat
- Path: sparky!uunet!brunix!cs.brown.edu!mpp
- From: mpp@cs.brown.edu (Michael P. Perrone)
- Subject: Re: Question on ratio estimate
- Message-ID: <1992Sep4.203740.25570@cs.brown.edu>
- Sender: news@cs.brown.edu
- Organization: Center for Neural Science, Brown University
- References: <huff-020992210907@pgl6.chem.nyu.edu> <87798@netnews.upenn.edu> <thompson.715495148@kiyotaki.econ.umn.edu>
- Date: Fri, 4 Sep 1992 20:37:40 GMT
- Lines: 15
-
- T. Scott Thompson writes:
- >To apply this to your problem let K = 2, J = 1 and set
- >Z_i = (X_i,Y_i). Set
- >
- > g(z) = z(1) / z(2) so that G = [ 1 / m(y), -m(x)/m(y)^2 ].
-
- but i thought that z(1) and z(2) may be correlated
- thus the i.i.d. assumption may be bad in general.
-
- if the z(1) and z(2) are i.i.d. then
- g(z) approaches a lorentzian distribution as n --> infinity
- since the z(1) and z(2) both approach gaussian distributions.
-
-
- - Michael
-