similar to: The 'REP' term in AMMI{agricolae}

Dear all! W2k, R 2.5.1 I am working with an ongoing malting barley variety evaluation within Sweden. The structure is 25 cultivars tested each year at four sites, in field trials with three replicates and 'lattice' structure (the replicates are divided into five sub blocks in a structured way). As we are normally keeping around 15 varieties from each year to the next, and take in 10 new

Hi, In this newsletter (Vol 7, 1),the article on AMMI by Onofri and Ciriofolo presented a AMMI function. One of arguments for this function AMMI (Page 17) is biplot. There is a biplot fucntion from {stats} package. I guess they are not the same. Could the authors clarify that? Thanks, Yuandan [[alternative HTML version deleted]]

Thanks a lot to Demitris for a prompt answer some minutes ago on another tread (see below). To avoid excess mails on the list, I move onto next question: I have another small plotting problem that confuses me. I want to plot results from a field trial series, using the numbers of the trials as symbols in the plot. pch = as.character(trial_no) works fine, but truncates the trial number to the

Dear all, W.XP I recently upgraded to R2.10.0 and did what I usually do: copied all "special" libraries from the old installation and then used "update.packages()" on the command line. Nothing happened. Then I clicked on the same command on the droplist which generated "update.packages(ask='graphics')", but still with no effect. When I tried to load the

Hello all, I posted a similar question recently but I suspect that it was not well enough formulated to trigger any answers. So I try again: Is there a way to produce boxplots (or something similar) that uses the estimated fixed effects of an lme{nlme} object? When I want to know the mean, I use estimable{gmodels} together with an appropriate matrix. I did look for a similar tool to estimable in

I have used the correlation analysis (pearson) in the agricolae package to analyse my data and got unexpectedly low p-values (therefore making many more highly significant correlations in my data than I had expected). I am wondering if the p-values given should be subtracted from 1 to give the real p-value, because for each variable compared against itself has a p-value of 1 and I thought it

Dear all R2.10 WinXP I have a dataset dealing with the way different wheat cultivars build their yield. Wheat ears are organised in spikelets where the spikelets can be numbered from the bottom, with even numbers on one side and odd on the other. I know how many kernels there were in each spikelet after some months spent counting them... Now I want to illustrate the differences between the

Cada vez que intento cargar el paquete "agricolae" me da el siguiente mensaje: Error: package or namespace load failed for 'agricolae' in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]): there is no package called 'spData' He intentado todo actualizar los paquetes, volverlos a instalar pero no hay forma. Si sabeis la solución ?? Un saludo. Juan

Dear list, I'd like to use path.analysis in the package agricolae in batch format on many files, retrieving the path coefficients for each run and appending them to a table. I don't see any posts in the help files about this package or the path.analysis package. I've tried creating an object out of the call to path.analysis, but no matter what I try, the function automatically prints

Hola a todos Estoy trabajando con el package agricolae para realizar pruebas de medias y obtengo un error que no entiendo al trabajar las interacciones. Os explico: Poseo un Diseño Completamente al Azar para el arreglo de tratamientos factorial de la forma 2*2*4. El modelo consta de 6228 observaciones, el esquema para el anova es: A= 2 niveles={2,5} B= 4 niveles={F1,F2,F3,F4} C= 2

Hello all, R2.2.1, W2k I posted a similar question last week after having problem with a group update (using update.packages()), without getting any answer. Now I have updated all packages separately, and found that the problem comes from nlme: Everything comes home, the md5 checksums are ok, but then the old version can??t be removed from my computer, leaving a "nlme" library with

Hi there, I am doing multiple comparisons for data that is not normally distributed. For this purpose I tried both functions kruskal{agricolae} and kruskalmc{pgirmess}. It confuses me that these functions do not yield the same results although they are doing the same thing, don't they? Can anyone tell my why this happens and which function I can trust? kruskalmc() tells me that there are no

Hello all, R2.1.1, W2k I try to make a plot of a simple regression model in this way: > with(njfA_bcd, { + plot(TC_OS.G31,Prot,cex = 2, col = "red", xlab= "TC/OS at GS32", + ylab="Grain crude protein (CP)") + }) This part works well and produces the datapoints as red circles. When I try to add a line, using a fitted linear model in a way that works perfect

Hello everybody! I use R 1.6.2 in Windows, and have a problem controlling the na.action. In a dataset with twelve trials, one of the trials lack any readings of the variable "STS.SH" (standing power at harvest) Fitting an aov() object with the call: led1t7sts.aov <- aov(STS.SH ~ Trial/Block + Treatment + Treatment:Trial, data = led1t7, na.action=na.exclude) seems to work as it

Hello all! R2.0.1, W2k. All packages updated. I?m heavily dependant on using mixed models. Up til?now I have used lme() from nlme as I have been told to. Together with estimable() from gmodels it works smooth. I also often run Rcmdr, mostly for quick graphics. After using Rcmdr, on reopening the R workspace all help libraries for Rcmdr (22 !) loads, among them nlme, but not Rcmdr itself. Why?

Hello all! I have a problem that calls for a better understanding, than mine, of how lme() uses the random part of the call. The dataset consists of eleven field trials (Trial) with three replicates (Block) and four fertiliser treatments (Treat). Analysing for example yield with lme() is easy: m1 <- lme(Yield ~ Treat, data=data, random =~1| Trial/Block) giving estimates of

Hello all! System: R2.0.1, W2k. All packages apdated with update.packages(). I use the default graphic device for my system (no active choice). I?m trying to fine-tune scatterplot() graphs (package car), for publication. I want to control plotting symbols and colours to match plots from other, less flexible, systems. I also need to make all text and symbols bigger, to enable printing of the

Hi Björn, 1) The pass pipeline syntax is documented here: https://github.com/llvm-project/llvm/blob/master/include/llvm/Passes/PassBuilder.h#L378 -die is not implemented, since the new pass manager does not support BasicBlock passes. But you can use dce instead: "-passes=dce" 2) I don't have a qualified answer here, but if I recall correctly, the trouble to correctly update the

Björn Pettersson A <bjorn.a.pettersson at ericsson.com> writes: > In llvm (split) we have: > > UL4->UL3->UL2->UL1->UL0 > \ > ...->DL2->DL1 > > In clang (split) we have: > > UC4->UC3->UC2->UC1->UC0 > \ > ...->DC2->DC1 > > > DL1 is a commit that updates the

Hello all, R2.1.1, Wk2 I am doing some two-step plotting, first using plot() to illustrate the datapoints and then using abline() to place a trend line from a fitted model into the plot. Everything works well as long as the formula of the fitted model i of the type: m1 <- lm(Dependent ~ Independent) then abline(m1) puts the proper straight line into the plot. But if I use: m2 <-