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Hi, Is it possible (i am sure it is) to subset data from a data.frame on the basis of SQL >LIKE< operator. I.e., i would like to subset a data where only values which contains a string >GP< would be used? Example: Gp<-subset(DF, DF$USCS like >GP<) This like of course is not working, Thanks, m [[alternative HTML version deleted]]

Hi Steven, Thank you for the help. I get an error though when i do this : >lit<-read.csv("litologija.csv", sep=";", dec=".") >sent <-data.frame(sentence=lit$Opis,stringsAsFactors=FALSE) >str(sent) >sentV<-rep(sent,10) >str(sentV) >first=second=third=fourth=fifth=sixth=seventh=eighth=ninth=tenth<-vector(length=10) >DF

Hi all, I am trying to test wheater the distribution of my samples is normal with QQ plot. I have a values of water content in clays in around few hundred samples. Is the code : qqnorm(w) #w being water content qqline(w) sufficient? How do I know when I get the plots which distribution is normal and which is not? Thanks, m [[alternative HTML version

Dear all, I tried to install gstat package and add the following compilation error : ------------------------> * Installing *source* package 'gstat' ... creating cache ./config.cache checking for gcc... gcc checking whether the C compiler (gcc ) works... yes checking whether the C compiler (gcc ) is a cross-compiler... no checking whether we are using GNU C... yes checking whether

hi all, I have a plot to which i would like to add text labels. And i cant find a way...here is the code : enaD2<-idw(D2~1, loca=dva, newdata=grd) pts = list("sp.points", dva, pch = 20, cex=1.5, col = "darkred spplot(enaD2, "var1.pred",sp.layout=pts, main = "globina 60 cm", sub="D2",

Hi all, I would like to create a scatter plot of two variables (y, x) whith third value (z) written on the plot? After that i would like to add a line (Y=0.7*(x-20)) to the graph. I tried plot(x~y) but there is no command for the third vairable to be shown on the graph also i can't find a way to add a Y=x*(0.7-20) to the chart. Thanks, m [[alternative HTML version

Hello r-help, I am having trouble installing the add-on package gstat. I suspect (but I'm not sure) that the trouble may be that it runs all the checks for gcc, then uses Intel's compiler to actually compile. I have not been able to successfully force it to use gcc to test that theory. R CMD INSTALL and R.version() output follow below; any help greatly appreciated! -Tim -- Timothy

Hi all, Is there a way to pass R code from web page (html file) to do some statistics and than plot the output in web browser. I am looking forever at this, and cant find a way. Regards,m -- View this message in context: http://r.789695.n4.nabble.com/Passing-R-code-from-webpage-tp4658800.html Sent from the R devel mailing list archive at Nabble.com.

Hi all, i have a data set cintaining 14 columns and 11 rows. Rows represent single point and columns represent the parameter measured. I wiuld like to compare the data to see which are more alike. I used the cluster analysis, but now i ma wondering if there are some other methods, since the cluster analysis did not give me the result i like. I tried to use factanal() for factor analysis

Dear all, I did post a message about problems on installing a package (gstat) which ends with a compilation error: ** libs gcc -I/usr/lib/R/include -mieee-with-inexact -fPIC -g -O2 -c block.c -o block.o gcc -I/usr/lib/R/include -mieee-with-inexact -fPIC -g -O2 -c chfactor.c -o chfactor.o gcc -I/usr/lib/R/include -mieee-with-inexact -fPIC -g -O2 -c copy.c -o copy.o gcc

H ello R-experts, I want to do ordination plots using vegan metaMDS. I have a where many cells have zero values. Data structure: X[1:10,1:14] Height.1 Height.2 Height.3 Height.4 Height.5 Height.6 Height.7 Height.8 Height.9 Height.10 Height.11 Height.12 Height.13 D30I1A 46 0 0 0 0 0 0 0 0 0 39 0 98 D30I1B

Dear all, I have just sent an email with my problem, but I think no one can see the red part, beacuse it is black. So, i am writing again the codes: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N <- 200 I <- 5 taus <- c(0.480:0.520) h <-

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

Dear all, I am a new user in r and I am facing some problems with the quantile regression specification. I have two matrix (mresultb and mresultx) with nrow=1000 and ncol=nsim, where I specify (let's say) nsim=10. Hence, the columns in my matrix represents each simulation of a determined variable. I need to regress each column of mresultb on mresultx. My codes are the following:

I?m working on an R-implementation of the simulation-based finite-sample null-distribution of (R)LR-Test in Mixed Models (i.e. testing for Var(RandomEffect)=0) derived by C. M. Crainiceanu and D. Ruppert. I'm in the beginning stages of this project and while comparing quick and dirty grid-search-methods and more exact optim()/optimize()-based methods to find the maximum of a part of the

## Package Needed library(fields) ## Assumptions set.seed(123) nsim<-5 p<-2 ## Generate Random Matrix G G <- matrix(runif(p*nsim),nsim,p) ## Set Empty Matraces dmax and dmin dmax<- matrix(data=NA,nrow=nsim,ncol=p) dmin<- matrix(data=NA,nrow=nsim,ncol=p) ## Loop to Fill dmax and dmin for(i in 1:nsim) { dmax[i]<- max(rdist(G[i,,drop=FALSE],G)) dmin[i]<-

Hello R-user community! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) Presently I try to run the function metaMDS (vegan) using an existing dissimilarity-matrix. As I would like to start with this matrix I thought I could just give the matrix using the x= -argument Test<-metaMDS(x=Dist.Gower) Fehler in inherits(comm, "dist") :

Running the function below, tested using the cardiff dataset from splancs generates the following error. What changes do I need to make to get the function to work? Thanks. --Dale > gen.rpoints(events, poly, 99) > rpoints Error: object "rpoints" not found # test spatial data library(splancs) data(cardiff) attach(cardiff) str(cardiff) events <- as.points(x,y) ###

Dear all, Does anyone have any idea on how to speed up the for() loop below. Currently it takes approximately 2 minutes and 30 seconds. Because of the size of Nsim and N, simulating a multivariate normal (instead of simulating Nsim times a vector of N normal distributions) would require too much memory space. Many thanks for your kind help, Simona N=3000 PD=runif(N,0,1) cutoff.=qnorm(PD)

Craig, Thanks for your follow-up note on using the asypow package. My problem was not only constructing the "constraints" vector but, for my particular situation (Poisson regression, two groups, sample sizes of (1081,3180), I get very different results using asypow package compared to my other (home grown) approaches. library(asypow) pois.mean<-c(0.0065,0.0003) info.pois <-