I would like to fit a glm with Poisson distribution and log link with a known
dispersion parameter. I do not want to estimate the dispersion parameter. I
know what it is, so I simply want to fix it at a constant for this and other
models to follow. My simple, no covariate model is:
Tall.glm<-glm(Seedling~1,
family=poisson,
offset(log(area)),
data=tallPSME.df)
I want to fix the dispersion parameter at 2.5. How can I do this, please?
Thanks in advance,
Manuela
>::<>::<>::<>::<>::<>::<>::<>::<>::<
Manuela Huso
Consulting Statistician
201H Richardson Hall
Department of Forest Ecosystems and Society
Oregon State University
Corvallis, OR 97331
ph: 541-737-6232
fx: 541-737-1393
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of L Brown
Sent: Tuesday, September 28, 2010 2:47 PM
To: r-help@r-project.org
Subject: [R] drawing samples based on a matching variable
Hi, everyone. I have what I hope will be a simple coding question. It seems
this is a common job, but so far I've had trouble finding the answer in
searches.
I have two matrices (x and y) with a different number of observations in
each. I need to draw a random sample without replacement of observations
from x, and then, using a matching variable, draw a sample of equal size
from y. It is the matching variable that is hanging me up.
For example--
> # example matrices. lets assume seed always equals 1. (lets also assume I
have assigned variable names A and B to my columns..)
> set.seed(1)
> x<-cbind(1:10,sample(1:5,10,rep=T))
> x
[A] [B]
[1,] 1 2
[2,] 2 2
[3,] 3 3
[4,] 4 5
[5,] 5 2
[6,] 6 5
[7,] 7 5
[8,] 8 4
[9,] 9 4
[10,] 10 1
> y<-cbind(1:14,sample(1:5,14,rep=T))
> y
[A] [B]
[1,] 1 2
[2,] 2 2
[3,] 3 3
[4,] 4 5
[5,] 5 2
[6,] 6 5
[7,] 7 5
[8,] 8 4
[9,] 9 4
[10,] 10 1
[11,] 11 2
[12,] 12 1
[13,] 13 4
[14,] 14 2
> #draw random sample of n=4 without replacement from matrix x.
> x.samp<-x[sample(10,4,replace=F),]
> x.samp
[A] [B]
[1,] 3 3
[2,] 4 5
[3,] 5 2
[4,] 7 5
Next, I would need to draw four observations from matrix y (without
replacement) so that the distribution of y$B is identical to x.samp$B.
I'd appreciate any help, and sorry to post such a basic question!
LB
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