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Re: Constrained non linear regression using ML
From: |
Jaroslav Hajek |
Subject: |
Re: Constrained non linear regression using ML |
Date: |
Tue, 23 Mar 2010 09:55:23 +0100 |
On Tue, Mar 23, 2010 at 9:33 AM, Corrado <address@hidden> wrote:
> Sorry, I am really lost here ....
>
> Jaroslav Hajek wrote:
>>>
>>> Yes and no. It's not a simple random variable, it's dependent on an
>>> n-dimensional vector p: Y = Y(p). In statistics this is usually called
>>> a "random field".
>>>
>
> What is p, and what is n?
p is from your original parametric model:
Y(p) = 1-exp(-(k0+k'*p)) + Yerr
where Yerr is a random variable (the error component), i.e. Y is a sum
of a function of p and an independent random variable.
--
RNDr. Jaroslav Hajek, PhD
computing expert & GNU Octave developer
Aeronautical Research and Test Institute (VZLU)
Prague, Czech Republic
url: www.highegg.matfyz.cz
- Re: Constrained non linear regression using ML, (continued)
- Re: Constrained non linear regression using ML, Fredrik Lingvall, 2010/03/17
- Re: Constrained non linear regression using ML, Michael Creel, 2010/03/17
- Re: Constrained non linear regression using ML, Fredrik Lingvall, 2010/03/18
- Re: Constrained non linear regression using ML, Corrado, 2010/03/18
- Re: Constrained non linear regression using ML, Fredrik Lingvall, 2010/03/19
- Re: Constrained non linear regression using ML, Corrado, 2010/03/19
- Re: Constrained non linear regression using ML, Fredrik Lingvall, 2010/03/19
- Re: Constrained non linear regression using ML, Corrado, 2010/03/23
- Re: Constrained non linear regression using ML, Jaroslav Hajek, 2010/03/23
- Re: Constrained non linear regression using ML, Corrado, 2010/03/23
- Re: Constrained non linear regression using ML,
Jaroslav Hajek <=
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