similar to: plot() and points() precision control

Dear R-Community! The example "oats" in MASS (2nd edition, 10.3, p.309) is calculated for aov and lme without interaction term and the results are the same. But I have problems to reproduce the example aov with interaction in MASS (10.2, p.301) with lme. Here the script: library(MASS) library(nlme) options(contrasts = c("contr.treatment", "contr.poly")) # aov: Y ~

Dear List, I have been using R to create an xyplot using the panel function within lattice libraries. This plot is based on the data supplied in R named 'Oats'. The graph represents oat yield by nitro level with an overlay of each variety of oats for each nitro level. I have three questions regarding this graph: 1) I cannot seem to specify the type of symbol used by the plot, even though

Dear R users, this is a follow up of this message http://tolstoy.newcastle.edu.au/R/e6/help/09/05/13897.html I'm reproducing the core of it for convenience. > // > / data(Oats, package = "MEMSS") / > / tp1.oats <- xyplot(yield ~ nitro | Variety + Block, / > / data = Oats, / > / panel = function(x, y, subscripts, ...) { /

Full_Name: Kevin Wright Version: 1.8.0 OS: Windows 95 Submission from: (NULL) (170.54.59.160) This bug also happens to me using R 1.9.0 on Windows 2000. Took me a long time to create a reproducible bug, but I think I have succeeded. I suspect my test function has a bug, but I don't see anything wrong. Plus, the bug only shows up when selecting certain filenames. Nearest I can speculate,

The following code produces a legend ("key") that mentions the unused levels of Block. library(MEMSS) xyplot(yield~nitro, subset=(Block=="I" | Block=="II"), data=Oats, group=Block, auto.key=T) and adding "drop.unused.levels=T" does not fix it. And in fact even the following does not solve the problem: xyplot(yield~nitro,

How would I set up a model stub so that <%= error_messages_for ''some_model'' %> doesn''t complain? I started going down this road: @some_model.stub! (:errors).and_return(ActiveRecord::Errors.new) but it seems like a long, hopefully uneccessary road. Cheers, Michael

I am trying to do Tukey HSD comparisons on a repeated measures expt. I found the following example on r-help and quoted approvingly elsewhere. It is broken. Can anyone please tell me how to get it to work? I am using R 2.4.1. > require(MASS) ## for oats data set > require(nlme) ## for lme() > require(multcomp) ## for multiple comparison stuff > Aov.mod <- aov(Y ~ N + V +

Dear all, Consider a completely randomized block design (let's use data(Oats) irrespoctive of the split-plot design it was arranged in). Look: library(nlme) fit <- lme(yield ~ nitro, Oats, random = ~1|Block, method="ML") fit2 <- lm(yield ~ nitro + Block, Oats) anova(fit, fit2) gives this: Model df AIC BIC logLik Test L.Ratio p-value fit 1 4 624.3245

When we call a lattice function such as xyplot, to what extent does the "data" designation cause the function to look inside the "data" for variables? In the examples below, the "subset" argument understands that "Variety" is a variable in the data. But the "scales" argument does not understand that "nitro" is a variable in the data.

Dear R users, I have a question about the patterned variance-covariance structure for the random effects in linear mixed effect model. I am reading section 4.2.2 of "Mixed-Effects Models in S and S-Plus" by Jose Pinheiro and Douglas Bates. There is an example of defining a compound symmetry variance-covariance structure for the random effects in a split-plot experiment on varieties of

Hi use Rs, I have a csv file: "1989-90","1990-91" Barley,23,34 Oats,15,16 Which I want to turn into: year, Barley, Oats 1 "1989-90", 23, 15 2 "1990-91",34,16 Transpose doesn't quite do it, is there a standard way? Cheers, Geoff Russell

I've looked through all the doc and searched the list archives, but I just can't seem to get it to work. I have a Linux box with 5 ethernet interfaces, 3 of which have winboxes I'd like to include in my little Samba network. I'm able to get it far enough for each winbox to see the linbox, but they can't see each other. Here's my setup: Winboxes Linbox Win2k -

im trying to deploy my app on our staging server and am running into an issue. we have a MySQL NDB cluster for the staging box. this basically means that the staging box should be able to use MySQL via localhost and it will automatically know it''s in a cluster. When running queries, it will go out to the real DB boxes instead of localhost to fetch the data. AFAIK, the clustering setup

Hello, can anybody tell me how to produce a plot like the one in http://cran.r-project.org/web/packages/lme4/vignettes/Implementation.pdf on page 13, Figure 6? The data is stored in: library(nlme) data(Oats) Cheers -- View this message in context: http://r.789695.n4.nabble.com/Help-needed-in-reproducing-a-plot-tp4119603p4119603.html Sent from the R help mailing list archive at

Dear all, I'm analysing a split-plot experiment, where there are sometimes one or two values missing. I realized that if the data is slightly unbalanced, the effect of the subplot-treatment will also appear and be tested against the mainplot-error term. I replicated this with the Oats dataset from Yates (1935), contained in the nlme package, where Variety is on mainplot, and nitro on

Hello, I am having a problem which stems from the fact that the Agents that handle my call queues are unaware if there are are people waiting in the queue. I have found the following configuration options but they are not very helpful. in queues.conf: announce=xxx The "announce = XXX" option in queues.conf makes Asterisk play the XXX announcement to the member of the queue who

Dear List, I have got error message when I run the R-code. Can anyone has a suggestion? v.code <- df.bm7[,c(10:31)]; v.code[1:3,] names(v.code) CM = v.code # variable binomial code sim.sp <- function(data,CM,n,N) { C <- matrix(rep(NA,N),ncol=1) for(i in 1:N) { j <- n xx <- which(colSums(CM[j,])==1) V <- names(xx) V <- paste(V,

When dtmfmode is set to inband for SIP, and i originate a call from sip out to the PSTN, I can hear the DTMF digit twice in the audio stream. Once very briefly and once for normal duration. Our Theory: While Asterisk is parsing the DTMF, for a fraction of a second, while the end user generated DTMF is being detected, the DTMF is passed inband. Once the DTMF is detected Asterisk silences it

hello, I'd like know how to do to extract data from a frame for example how can I do to extract only the data where variety=victory or variety=golden rain thanks. > Oats Block Variety nitro yield 1 I Victory 0.0 111 2 I Victory 0.2 130 3 I Victory 0.4 157 4 I Victory 0.6 174 5 I Golden Rain 0.0 117 6 I Golden Rain

Dear R-help, Why can't lme cope with an incomplete whole plot when analysing a split-plot experiment? For example: R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.1 (2006-06-01) > library(nlme) > attach(Oats) > nitro <- ordered(nitro) > fit <- lme(yield ~ Variety*nitro, random=~1|Block/Variety) > anova(fit) numDF denDF F-value