similar to: Problem Connecting to Oracle with R from Windows XP

Dear all, I have a data frame with one factor and four numeric variables and wish to obtain the var-cor matrix separately by factor. I tried by() and sapply() but getting nowhere. I understand this can be done by subsetting the dataframe, but there should have some sleek ways of doing it. Here is a simulated dataframe; s <- rep(c("A","B","C"), c(25,22,18)) d

Dear forumities, It's seem that there is no straight forward way to calculate R2 of a cluster solution in R. So, I would like to know if I'm right when calculating a R2-like statistic for a given clustering solution. In fact, I have different cluster solution for a given set of data. I would like to know which cluster solution gives the highest R2. My data (5 variables) are scaled to a 0

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

Dear list, I'm plotting a lattice plot xyplot(Volume ~ Weight | as.character(DateTime)) where DateTime is a POSIXlt object. This produces strip labels in the format e.g. "2007-11-15 23:15:00" and panels are plotted in the correct order. I'd prefer a format "15 Nov 23:15", but if I use format(DateTime,format="%d %b %H:%M") to do the conversion, then the

Dear list, When I try to use lines.formula with subset and another argument I get an error. e.g. x<-1:5 y<-c(1,3,NA,2,5) plot(y~x, type="n") # set up frame lines(y~x, subset=!is.na(y)) # works OK lines(y~x, type="o", col="blue") # works OK # but lines(y~x, subset=!is.na(y), col="red") # gives an error: Error in if (length(x) == l) x[s] else x :

Hi R help, I'm a fairly experienced R user but this manipulation has me stumped, please help: DATA id<-rep(LETTERS[1:5],20) distance<-rnorm(1:100, mean = 100) bearing<-sample(1:360,100,replace=T) month<-sample(1:12,100,replace=T) I have a dataset with records of individuals (id) , each with a distance (distance) & direction (bearing) recorded for each month (month). I want

I am not getting much benefit from using oplocks = False or dos filetime resolution = True in Samba 1.9.18p3 on Solaris 2.5.1 and the Developer Studio in Digital Visual Fortran (v6.0) on WinNT4,SP4. I am also setting my PC clock to the samba server. I still get a lot of messages from the Studio informing me the source code files and workspaces have changed outside the editor or Studio

Dear all; Searching the R site for answers to my problem, but found none. Here is the run and error: > bwplot(dev ~ Dbhcl | Period, data = DbhValid2, font = 2, + main=list(" "), axis.font =2, + ylab = list(label = "Residual (cm)", font = 2), + xlab = list(label = "Dbh class (cm)", font = 2), + par.strip.text=list(cex=0.8, font=2), + panel=function(x,

Dear All; I tried to use fitdistr() in the MASS library to fit a mixture distribution of the 3-parameter Weibull, but the optimization failed. Looking at the source code, it seems to indicate the error occurs at if (res$convergence > 0) stop("optimization failed"). The procedures I tested are as following: >w3den <- function(x, a,b,c)

Andrew: Differentiated Service on Linux HOWTO (work in progress) could be of some help for you. Have a look at http://opalsoft.net/qos Best regards, Leonardo Balliache >Message: 6 >From: "Burnside, Andrew" <Andrew.Burnside@thalesgroup.com> >To: "''lartc@mailman.ds9a.nl''" <lartc@mailman.ds9a.nl> >Date: Wed, 18 Jun 2003 13:24:44

Dear All; Searching on the achieve, many questions on optim() have been asked, but I haven't seen the following. The question began with my original inquiry on "Optimization failed in fitting mixture 3-parameter Weibul l distribution using fitdistr()" which I posted on Jul. 28, Prof. Ripley kindly advised me to look into options of optim() for the answer. Following his advice and

Hi, I'm dealing with wind data and I'd like to model their distribution in order to simulate data to fill-in missing values. Wind direction are typically following a vonmises distribution and wind speeds follow a weibull distribution. I'd like to build a joint distribution of directions and speeds as a VonMises-Weibull bivariate distribution. First is this a stupid question? I'm

Dear R list, The code below puts qq-plots for two of three groups on the one plot. However the legend includes all three groups, ie the auto.key ignores the subset instruction. Is there an easy way to get around this, so that only those groups plotted are included in the legend? y1<-rnorm(100); y2<-rnorm(100)+1; y3<-rnorm(100)+2; y<-c(y1,y2,y3)

Hello, I am beginning with R and I would like to test a non linear model. But I do not find exactly wath I am looking for in nls packages (or I do not know where to search). I would like to try a model like this : y=b * x exp(n)/(a exp(n) + x exp (n)) Where a = a0 + a1z b= b0 + b1z x and z are variables y the variable that I am trying to modelise a0, a1, b0 and b1 are parameters to determine. I

R-helpers; I tried to get a superscripted 3 in the following xyplot example but failed: >data(whiteside) >xyplot(Gas ~ Temp | Insul, whiteside, panel = function(x, y, ...) { panel.xyplot(x, y, ...) panel.lmline(x, y, ...) }, xlab = "Average external temperature (deg. C)", ylab = paste(paste("Gas consumption (1000", expression(ft^3),")"), aspect

Dear All; While using EMclust() in the mclust package, I frequently encountered a program error. A message window popped up with the message " Rgui.exe has generated errors and will be closed by Windows. You will need to restart the program. An error log is be created." > version _ platform i386-pc-mingw32 arch i386 os mingw32

This may seem to be an odd request, but here it goes: I would like to be able to recursively load pxelinux. Simple reason being that many useful mini distro's now use it (PXES, Recovery is Possible, Fedora Anaconda, my own homebrew setup program, unattended.sf.net, etc), and I would like to be able have drop in upgradabily for those distro's. The idea being I can create a master menu and

Dear all; Using read.ssd, I tried to import a SAS dataset from a network drive; an error occurred: > stemattr <- read.ssd("g:/olmn2/dyang/siteprod/datasasv8", "stemattr") SAS failed. SAS program at C:\DOCUME~1\dyang\LOCALS~1\Temp\file7785.sas a log and other error products should be in the vicinity Warning messages: 1: sas not found 2: ls not found 3: SAS return

Dear R list members; I have a 10 x 423 data frame which consisting of response, time, subject, site, plot and covariates (continueous and categorical) measured at the plot level. When the data frame was converted into a groupedData object, a warning appeared > A <- groupedData(ht ~ time | Subject, data = tt, outer = ~ site * plot, + labels=list(y = "Height", x =

Dear all; I experienced a memory allocation error while running gnls: > wBlplfe.wc <- update(wBlplfe.w, corr=corAR1()) Error: cannot allocate vector of size 37950 Kb In addition: Warning message: Reached total allocation of 256Mb: see help(memory.size) Increased memory limit to 512, 640 M, the allocation error persisted: > memory.limit(512) NULL > wBlplfe.wc <-