Thanks to Bill Dunlap and Avi Gross for their clear and helpful answers
to my questions.
cheers,
Rolf Turner
--
Honorary Research Fellow
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
__
R-help@r-project.org mailin
Look here:
https://cran.r-project.org/web/views/NaturalLanguageProcessing.html
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Tue, Jul 20, 2021 at 8:47 AM Br
The mixed models list is r-sig-mixed-models .
nlme:lme is not really designed for crossed random effects. IIRC, it's
possible, but not easy. As Kevin said, lme4:lmer is really what you should
use.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking thi
You might get better answers on the r-sig-ME list.
The lmer() function from lme4 handles crossed and non-nested random effects
quite seamlessly. I cannot comment on whether or not lme() can as well.
--
Kevin E. Thorpe
Head of Biostatistics, Applied Health Research Centre (AHRC)
Li Ka Shing Kno
Hi Brian. I assume you're interested in some kind of classification of
the theme or the contents within each document?
In which case I would direct you to natural language processing for
multinomial classification of unstructured data. Basically an NLP
(natural language processing) classifica
Hi,
I am wondering if there is some references on how R can be used to
analyse legal/court documents. I searched a bit in internet but unable
to get anything meaningful.
Any reference will be very appreciated.
Thanks for your time.
Thanks and regards,
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Dear R project,
I am a doctoral student in Zhejiang university in China, I am using lme
function in nlme package and learning the function by Package 'nlme' document.
I am writing this email for some help to build a lme model.
My goal was to include two non-nested random effects in the lme mode
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