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and
arbitrarily-scaled penalty matrices?
I apologise if I am wasting your by making an obvious mistake. I am a
clinician, not a statistician. So, I do not understand the mathematics.
Thanks, in advance, for your help,
Jonathan Williams
for estimates of the accuracy of an ordinal
gold standard?
Thanks, in advance, for your help,
Jonathan Williams
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)} ).
Thanks, in advance, for your help,
Jonathan Williams
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)} ).
Thanks, in advance, for your help,
Jonathan Williams
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Dear Helpers,
I was trying to find a repository of earlier Windows versions of R packages.
However, while I can find the Archives for Linux versions (in the Old Sources
section of each package's Downloads) , I cannot find one for Windows versions.
Does such a repository exist? If so, where can
with
m2 or when comparing m3 with m4.
With many thanks, in anticipation of your help in explaining this,
Jonathan Williams
Here is a simple sample code to generate the discrepancies:-
set.seed(1)
A=factor(rep(c(1:5),600))
B=factor(rep(c(0:2),each=1000))
b=as.numeric(as.character(B))
C=factor
Thanks Don MacQueen for this reply to my initial query - please SEE MY REPLIES
TO THESE IDEAS AND FURTHER INFORMATION BELOW
From: Don MacQueen [m...@llnl.gov]
Sent: 23 February 2010 21:25
To: Jonathan Williams; r-help@r-project.org
Subject: Re: [R] Problem with strptime generating missing
]).
Anything else that I try returns an error (e.g. xlab=expression(A
beta[1]42]) returns 'Error: unexpected symbol').
So, I would be very grateful if someone can tell me how to write my label.
Thanks,
Jonathan Williams
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Dear R Helpers,
Is there a way to generate multivariate correlated binomial data in R, similar
to how the rmvbin procedure in package bindata can generate multivariate
correlated binary data?
Thanks for your help,
Jonathan Williams
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of BIC and logLik.
Am I doing something wrong, here? If not, which are the real AIC and logLik
values for the different models?
Thanks for your help,
Jonathan Williams
Output:-
fit0=lmer(y~x1+x2+(1|id), data=datx); print(summary(fit0),corr=F)
Linear mixed model fit by REML
Formula: y ~ x1 + x2
with family=quasi... But, I
may be wrong. If you get more information about this from the great man, then
would you please let me know?
Thanks,
Jonathan Williams
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PLEASE do read
be one at location 4
# but regexpr gives 1 at location 1
#[1] 1
#attr(,match.length)
#[1] 1
Sorry if I am missing something obvious. I'd be very grateful if someone
would
please show me how to use regexpr to locate '.' in my string!
Thanks,
Jonathan Williams
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