Displaying 6 results from an estimated 6 matches similar to: "two lme questions"
2004 Apr 08
0
lme, mixed models, and nuisance parameters
I have the following dataset:
96 plots
12 varieties
2 time points
The experiment is arranged as follows:
A single plot has two varieties tested on it.
With respect to time points, plots come in 3 kinds:
(1) varietyA, timepoint#1 vs. variety B, timepoint#1
(2) varietyA timepoint #2 vs. varietyB timepoint #2
(3) varietyA timepoint #1 vs. variety A timepoint#2
- there are 36 of each kind
2004 Mar 19
1
lme: simulate.lme in R
The goal: simulate chi square mixture distributions as a way of
simulating likelihood ratio test statistics for some mixed models where
the more specific model has some zero variance components (a la Pinheiro
and Bates pg. 84-87)
The problem: R doesn't have the function ms which is apparently used by
simulate.lme
In the current version of nlme for R, is there a way around this? Is it
2004 Feb 07
1
display functions in groupedData and lme
I'm trying to set up a mixed model to solve using lme. It will have 3
fixed effects, two random effects and two interaction terms.
I've been reading Pinheiro's and Bates's book on the nmle library, but
find the part about display functions to be unclear. When creating a
groupedData object from a data.frame, you need to enter a function of the
form: response ~primary|grouping
2016 Apr 27
2
odd behavior of numeric()
Why does:
> numeric(0.2*25)
return
[1] 0 0 0 0 0
but
> numeric((1-0.8)*25)
returns
[1] 0 0 0 0
[running version 3.2.0]
[Apologies if this has been asked before - it's a hard question to find
specific search terms for]
Thanks,
Scott
2007 Dec 12
1
problems with rsync 2.6.9 and large files (up to 20GB)
Hi,
I'm Jordi and I work at the university of barcelona. I'm trying to make a
backup of our several clusters. In the past I worked with rsync with a very
good results.
When I try to backup some large directories (for example > 1.5TB with a lot
of large files >20GB) whit this command:
rsync -aulHI --delete --partial --modify-window=2 --log-format=" %t %o %l %f
" -
-stats
2006 Dec 28
0
lmer: Interpreting random effects contrasts and model formulation
I'm trying to fit a nested mixed model using lmer and have some
questions about the output and my model formulations.
I have replicate measures on Lines which are strictly nested within
Populations.
(a) So if I want to fit a model where Line is a random effect and
Populations are fixed and the random Line effect is constant across
Populations, I have:
measure_ijk = mu + P_i + L_ij +