Displaying 5 results from an estimated 5 matches for "rcbd".
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rbd
2012 Nov 27
2
Help with graphics in gamm4 library
My problem is relatively straight forward, but I cannot seem to find a way to
make it work.
I have a RCBD with repeated measurements over time. I have created a fit
using the gamm4 package. My model is:
fit4a <- gamm4(Rate ~ s(Time,by=trt,bs="cr")+trt,data=qual.11.dat,
random=~(1|block),correlation=corARH1())
What I would like to create is plots with the X-axis being tim...
2017 Nov 14
0
Possible bug(s) causing ggplot2 and XLConnect to crash recent builds of r-devel
The following R code causes R to crashes under recent r-devel builds of R:
library(ggplot2)
RCBD.lay <- data.frame(Blocks = factor(rep(1:5, each = 6)),
Units = factor(rep(1:6, times = 5)),
Treatments = factor(rep(1:6, times = 5)))
ggplot(data = RCBD.lay, aes(x = Units, y = Blocks, label = Treatments)) +
geom_text(aes(colour = Treatments))
I...
2010 Dec 13
0
SAS "/slice" and "/diff" equivalent? - Automated multiple comparisons in nlme package?
...e() :
###R code:
model <- lme( y ~ g + h + yr + yr:h, random = ~ 1 | b, data = yield)
*** SAS code:
proc mixed data=yield covtest cl method=reml;
class b g h yr;
model y = g h yr yr*h;
random b;
lsmeans g / diff;
The codes above give equivalent outputs (analysis of a 5(g) by 2(h)
factorial, RCBD(b)), except for the "lsmeans g / diff" line, which I
cannot reproduce in R!
The below gives one of the comparisons I am looking for.
anova(model, L=c("gPEN"=1, "gC5"=-1))
Is there a command to automate such thing? I understand from
https://stat.ethz.ch/pipermail/r-h...
2009 Feb 04
0
R-Package ScottKnott
...ottKnott now implemented at CRAN. The
package uses the SkottKnott clustering algorithm to perform multiple
comparison tests of means using the following experimental designs:
Completely Randomized Design (CRD); Factorial Experiment (FE); Latin Squares
Design (LSD); Randomized Complete Block Design (RCBD); Split-Plot Experiment
(SPE); Split-Split-Plot Experiment (SPE). One of the great qualities of
this test is that it produces no overlapping whatsoever so that the groups
of means are always mutually exclusive.
The results will appear in both the usual way (using letters to name the
groups) and in...
2010 Mar 31
1
trying to understand lme() results
Hi, I have very simple balanced randomized block design where I total have 48 observations of a measure of weights of a product, the product was manufactured at 4 sites, so each site has 12 observations. I want to use lme() from nlme package to estimate the standard error of the product weight.
So the data look like:
MW site
1 54031 1
2 55286 1
3 54396 2
4 52327 2
5 55963