similar to: Line width through plot size reduction

Dear ALL, I fear my question has already been answered many times before, but I haven't fund that in archives... I am working on spatial datasets and, in most arrays I'm handling, there are two columns dedicated to (x,y)-coords. For different reasons - notably to draw image() plots, I need to have these two columns sorted in increasing order. But sort() and order() seem to apply to

I cannot operate lattice plots, notably those in package gstat, within for() loops. (I can neither read such graphics included in a .R (or .txt) file with the source() function). However same commands executed one by one don't fail. Could you please help me find a means to execute lattice plots inside a loop ? Jacques VESLOT CIRAD -----------------------------------------------------

JGR has an fairly intelligent editor, and it works on Mac. Andy > From: Sean Davis > > Consider using ESS and xemacs or emacs. You get syntax highlighting, > auto-indent, command auto-complete, transcripts for your session, > integrated help, and the tools of one of the most powerful > text editors > on the planet. The learning curve is a bit steep, but if you use R

Dear all, I tried to use layout argument in xyplot to get one panel per page. I have a dataframe named 'data' with the following variables: x, y = coords, sub, bloc = 2-level factors, etat = 5-level factor, I did : > lset(theme = col.whitebg()) > xyplot(y ~ x | bloc*sub , data=data, groups=etat, + layout=c(0,1,4), + main="Etat des plantes dans chaque

Dear all, I have a matrix X with 47 lines and say 500 columns - values are in {0,1}. I'd like to compare lines. For that, I first did: for (i in 1:(dim(X)[1]-1)) for (j in (i+1):dim(X)[1]) { Y <- X[i,]+Y[j,] etc. but, since it takes a long time, I would prefer avoding loops; for that, my first idea was to add this matrix: X1=X[,rep(1:46,46:1)] to this one: res=NULL for (i in

Dear R-users, Is there an easy way to avoid points one upon another when ploting rows and columns of 'dudi' objects ? Maybe there is a function in ade4 or in an other package, or maybe someone has his or her own function to do this (for example to automatically modify a little the coordinates of these points to get a readable plot ?). Thanks in advance. Best regards, Jacques VESLOT

I am sorry to ask such question, but I can't find a solution... I have a dataframe 'd2004' and I want to remove two columns: 'd2004$concentration' and 'd2004$stade". I could do it just as follows: > names(d2004) [1] "Localite" "Date" "parcelle" "maille" "presence.plant"

Hi, Use Newdata <- subset(d2004, select=-c(concentration,stade)) See ?subset for details Best, Matthias > -----Urspr??ngliche Nachricht----- > Von: Jacques VESLOT [mailto:jacques.veslot at cirad.fr] > Gesendet: Donnerstag, 09. September 2004 12:38 > An: r-help at stat.math.ethz.ch > Betreff: [R] Indexing dataframe > > > I am sorry to ask such question, but I

Hi, I would like to be able to use R with a connection to a PostgreSQL database. I am using R 2.0.1 on windows XP. I have tried installing both the DBI and rDBI packages (which is better?) but in either case I run into the same problem - when i try to use either the dbDriver or dbConnect functions i'm told the function couldn't be found. Seems like the packages aren't installing

Dear All, I have a data, suppose it is an N*M matrix data. All I want is to classify it into, let see, 3 classes. Which method(s) do you think is(are) appropriate for this purpose? Any reference will be welcome! Thanks! Best, Baoqiang Cao

Hi, I got the following error message when running a function of mine doing intensive computations: Erreur dans .Call("R_lazyLoadDBfetch", key, file, compressed, hook, PACKAGE = "base") : r?f?rence d'argument par d?faut r?cursive I haven't found neither where the problem lies nor what could be recursive. Besides, I wonder whether it might or not be a problem

Dear R-users, My question is how to get right F tests for random effects in random effect models (I hope this question has not been answered too many times yet - I didn't find an answer in rhelp archives). My data are in mca2 (enc.) : names(mca2) [1] "Lignee" "Pollinisateur" "Rendement" dim(mca2) [1] 100 3 replications(Rendement ~ Lignee *

Dear all, I'm used to draw bubble plots (gstat) to get a first view of my spatial marked data, but I can't find a way to label legend with marks after having replaced them by a numeric scale. I have a data frame with numeric coords and factors: > names(data) [1] "x" "y" "bloc" "sub" "inoc"

Dear R-users, Sorry for reposting. I put it in another way : I want to test random effects in this random effect model : Rendement ~ Pollinisateur (random) + Lignee (random) + Pollinisateur:Lignee (random) Of course : summary(aov(Rendement ~ Pollinisateur * Lignee, data = mca2)) gives wrong tests for random effects. But : summary(aov1 <- aov(Rendement ~ Error(Pollinisateur * Lignee), data =

Dear all, I have a dataset with qualitative variables (factors) and I want to test the null hypothesis of independance between two variables for each pair by using appropriate tests on contingency tables. I first applied chisq.test and obtained dependance in almost all cases with extremely small p-values and warning messages. > chisq.test(table(data$ins.f, data$ins.st))$p.val [1]

Hi R guru coders I wrote a bit of code to add a new column onto a "topTable" dataframe. That is a list of genes processed using the limma package. I used a for loop but I kept feeling there was a better way using a more vector oriented approach. I looked at several commands such as "apply", "by" etc but could not find a good way to do it. I have this feeling there

I partly answered my question since independence_test() function in coin package apparently do Cochran-Armitage trend test just like Eric Lecoutre's function tabletrend() - slightly modified here: > independence_test(pheno ~ geno, data = dat2, teststat = "quad", scores = list(geno = c(0, 1, 2))) Asymptotic General Independence Test data: pheno by groups 1 < 2

Dear Tobias, I finally succeeded in exporting my dataframes from R into Access with this script: library(RODBC) canal <- odbcConnectAccess("D:/Floristique.mdb") sqlSave(channel=canal, dat=flore, tablename="Floristique", rownames=F, safer=F, fast=F, varTypes=c(dates="Date")) odbcClose(canal) My problem in exporting my dataframe "flore" seems to

Hi all, I have a very large binary vector, I wish to calculate the number of 1's over sliding windows. this is my very slow function slide<-function(seq,window){ n<-length(seq)-window tot<-c() tot[1]<-sum(seq[1:window]) for (i in 2:n) { tot[i]<- tot[i-1]-seq[i-1]+seq[i] } return(tot) } this works well for for reasonably sized vectors. Does

Dear all, I have the following data frame: > raw.count Var1 Freq 1 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA 707 2 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC 14 3 AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAT 3 But why when printint it using 'cat', it doesn't print the desired string "AAA" ? > cat(raw.count$Var1,