Hi,
Did you get this dealt with OK.
Cheers,
Dave
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> -Original Message-
> From: Joke Allemeersch [mailto:[EMAIL PROTECTED]
> Sent: Thursday, July 17, 2003 11:58 AM
> To: [EMAIL PROTECTED]
> Subject: [R] univariate norma
Did you search "www.r-help.org" -> Search -> "R Site Search" and
S-News (Google -> S-News -> S-News Mailing List Archives)?
I recently estimated a normal mixture, 2 components, mean 0,
different variances. I had computational difficulties until I took the
time to avoid under and overflow
I'll be in the lab in roughly 45 minutes, so I'll
boot Frothie back up. Egads, no one can access my
394 website!! What will they do??
R
_
Motorcycles are everywhere!
Check twice; save a life.
Rob Keefe Lab: (208) 885-5165
M.S.
Well,
If k is known, you can use maximun likelihood to fit the weights, means,
and sd's. The EM algorithm can be of help to solve the optimization
problem. You would have to implement it yourself for your particular
case, but I do not think it is big trouble.
Then you could estimate k using Ba
Hello,
I have a concrete statistical question:
I have a sample of an univariate mixture of an unknown number (k) of
normal distributions, each time with an unknown mean `m_i' and a
standard deviation `k * m_i', where k is known factor constant for all
the normal distributions. (The `i' is a sub
