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RE: st: RE: loglink and normality, mixed model
From
"Feiveson, Alan H. (JSC-SK311)" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
RE: st: RE: loglink and normality, mixed model
Date
Mon, 24 Feb 2014 15:08:02 +0000
Hi Ruud - OK - I agree, that log(EY) is what you say and that depending on e[i,j], Y =can be non-positive. I assume that Y is regarded as continuous if Y > 0. But you also said you had a number of cases with Y = 0. This can't happen unless e[i,j] is a mixture of a discrete and continuous distribution, In that case, I would think glm would have problems because it (glm) is designed for distributions from an exponential family.
Al
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Ruud van Lieshout
Sent: Monday, February 24, 2014 8:34 AM
To: [email protected]
Subject: Re: st: RE: loglink and normality, mixed model
Dear Al,
thank you for your response. I do indeed mean an additive eps. The expectation of Y is therefore equal to a*t^b and the log of the expectation is then equal to log(E(Y))=log(a)+b*log(t). Im NOT transforming the observation itself, just its expectation.
regards,
Ruud
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