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Not sure why you feel the need to use gnm here - are you working with non-normal data? From your description it would seem that nls is more appropriate,
 
Heather

Dr H Turner
Research Fellow
Dept. of Statistics
The University of Warwick
Coventry
CV4 7AL

Tel: 024 76575870
Fax: 024 76524532
Url: www.warwick.ac.uk/go/heatherturner



-----Original Message-----
From: Ronaldo Prati [mailto:prati@icmc.usp.br]
Sent: Thu 14/12/2006 13:41
To: r-help@stat.math.ethz.ch
Subject: [R] Model formula question
 
Hi all,

I'm not familiar with R programming and I'm trying to reproduce a
result from a paper.

Basically, I have a dataset which I would like to model in terms of
successive increments, i.e. (y denote empirical values of y)

y_1 = y1,

y_2 = y1 + delta1,

y_3 = y1 + delta1 + delta2.

..

y_m = y1 + sum_2^m delta j

where delta_j donote successive increments in the y-values, i.e.

delta j = y_j - y_(j-1).

In order to estimate y-values, I'm assuming that delta j is
approximately equal to kj**u, such that my regression model should be
something like this:

^y_1 = a1

^y_2 = a1 + k2**u

^y_3 = a1 + k2**u + k3**u

..

^y_m = a1 + k2**u + k3**u + ... + km**u

or, generically

^yi = a1 + k * sum_j=2^i  j**u

and I need to fit a non-linear least-squares regression model to find
the tripplet a1,k,u. I had a look to the gnm package, but I don't have
the lesser idea how to formulate this problem to use this package. Can
someone help me with that?

cheers,

Ronaldo




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