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faurby
2009 Jan 06
4
Apparant bug in binomial model in GLM (PR#13434)
Full_Name: S?ren Faurby
Version: 2.4.1 and 2.7.2
OS:
Submission from: (NULL) (192.38.46.92)
There appear to be a bug in the estimation of significance in the binomial model
in GLM. This bug apparently appears when the correlation between two variables
is to strong.
Such as this dummy example
c(0,0,0,0,0,1,1,1,1,1)->a
a->b
m1<-glm(a~b, binomial)
summary(m1)
It is sufficient that all
2011 Feb 20
8
Generating uniformly distributed correlated data.
I wish to generate a vector of uniformly distributed data with a
defined correlation to another vector
The only function I have been able to find doing something similar is
corgen from the library ecodist.
The following code generates data with the desired correlation to the
vector x but the resulting vector y is normal and not uniform
distributed
library(ecodist)
x <- runif(10^5)
y
2009 Dec 17
4
Fishers exact test at < 2.2e-16
In an effort to select the most appropriate number of clusters in a
mixture analysis I am comparing the expected and actual membership of
individuals in various clusters using the Fisher?s exact test. I aim
for the model with the lowest possible p-value, but I frequently get
p-values below 2.2e-16 and therefore does not get exact p-values with
standard Fisher?s exact tests in R.
Does anybody know