similar to: R's RNG produced garbage when called from f77 (Irix)

R 1.7.1 on Windows XP The "normal Q-Q plot" produced by plot.lm() mislabels points when the model is fitted using na.action=na.exclude. Example: x <- 1:50 y <- x + rnorm(50) y[c(5,10,15)] <- NA # insert some NA's y[40] <- 50 # add an outlier plot(lm(y ~ x, na.action=na.omit)) # outlier correctly labeled in all # four plots

Hello everybody When I try to connect (net use) a samba share (Acl protected) from a windows XP workstation I obtain the following message in the "/var/log/samba/workstation_name.log" : . . . [2004/01/15 11:12:44, 0] smbd/sec_ctx.c:initialise_groups(244) Unable to initgroups. Error was Operation not permitted . . . The network connection to this share run sucessfully but when I

Hello All: Has anyone configured a meetme conference to use video? I have successfully used video phones to talk through *, but I cannot seem to get video when those phones dial into a meetme conference. Is there something else that I need to be doing other than set the "v" flag on my extension for the meetme app? Thanks, Tim

Hi all, I am trying to play around with the randomForest function for classification. I know its performance is great. I am currently using the default options. It has many options. How do I further tweak the options so that I can make its performance even better? What are the options that are mostly used? Thanks a lot! M [[alternative HTML version deleted]]

When I try to open a server socket on the system setup listed below, I get the following error: > a <- make.socket(port=8091,server=TRUE) Error in make.socket(port = 8091, server = TRUE) : sockets are not available on this system I just wanted to make sure that sockets were generally available for this platform (or, perhaps, I need to upgrade to 1.2.2 on this system), before I got

Hi all, There is now a package available on CRAN that provides an R interface to Leo Breiman's random forest classifier. Basically, random forest does the following: 1. Select ntree, the number of trees to grow, and mtry, a number no larger than number of variables. 2. For i = 1 to ntree: 3. Draw a bootstrap sample from the data. Call those not in the bootstrap sample the

Hi all, There is now a package available on CRAN that provides an R interface to Leo Breiman's random forest classifier. Basically, random forest does the following: 1. Select ntree, the number of trees to grow, and mtry, a number no larger than number of variables. 2. For i = 1 to ntree: 3. Draw a bootstrap sample from the data. Call those not in the bootstrap sample the

Dear list, could someone point me to the normal score transform and it's use in R? I would like to transform my data with normal score transform, do some geostatsitical predictions and would like to transform the estimated values back including the estimation variance. Any suggestions? Ulrich -- __________________________________________________ Ulrich Leopold MSc. Department of

Dear R-users, I don't know if there is a problem in wtd.quantile (from library "Hmisc"): -------------------------------- x <- c(1,2,3,4,5) w <- c(0.5,0.4,0.3,0.2,0.1) wtd.quantile(x,weights=w) ------------------------------- The output is: 0% 25% 50% 75% 100% 3.00 3.25 3.50 3.75 4.00 The version of R I am using is: 2.1.0 Best,Jing

Hi, I am trying to install R 1.4.1 on and SGI using 64 bit. When I configure I get... R is now configured for mips-sgi-irix6.5 Source directory: . Installation directory: /usr/local C compiler: cc -64 -OPT:IEEE_NaN_inf=ON -g C++ compiler: CC -OPT:IEEE_NaN_inf=ON -g FORTRAN compiler: f77 -OPT:IEEE_NaN_inf=ON -g X11 support:

Hello I would like to see the algorithm that R uses to generate density functions for several distributions (i.e. Normal,Weibull, etc). I tried: >dnorm function (x, mean = 0, sd = 1, log = FALSE) .Internal(dnorm(x, mean, sd, log)) <environment: namespace:stats> How can I see the code used for densities? Thanks!

I try to use ?randomForest to find variables that are the most important to divide my dataset (continuous, categorical variables) in two given groups. But when I plot the outliers: plot(outlier(FemMalSex_NAavoid88.rf33, cls=FemMalSex_NAavoid88$Sex), type="h",col=c("red","green")[as.numeric(FemMalSex_NAavoid88$Sex)]) it seems to me that all my values appear as

Dear R-help, Yes, I do know about the auto-loading feature. My question is more complicated than that: Suppose I loaded a package (e.g., e1071) and created an object of certain class (e.g., svm), for which there is a print method in the package to hide things that the user may not need to see (e.g., large vectors or matrices needed by methods such as predict). If the next time I started R, I

Hello, I wrote the function below to integrate polysplines and thought that it may be useful to others. Please consider this code released under the GPL2 or later. Thanks, Bill <<integrate.polySpline.R>> Notice: This e-mail message, together with any attachments, contains information of Merck & Co., Inc. (One Merck Drive, Whitehouse Station, New Jersey, USA 08889), and/or

(Sorry for the cross-post--- I wasn't sure which list is more appropriate...) Hi everyone, I've run into segfaults when using my randomForest package on large dataset (e.g., 100 x 15200) and large number of trees (e.g., ntree=7000 and mtry=3000). I'm wondering if anyone can give me some hints on where to look for the problem. The randomForest package mainly consists of two things:

(Sorry for the cross-post--- I wasn't sure which list is more appropriate...) Hi everyone, I've run into segfaults when using my randomForest package on large dataset (e.g., 100 x 15200) and large number of trees (e.g., ntree=7000 and mtry=3000). I'm wondering if anyone can give me some hints on where to look for the problem. The randomForest package mainly consists of two things:

Dear R-help, I was able to build R-1.5.0 on WinNT w/o problem (actually it seems easier than previous version). However, I encountered problem when trying to compile the recommended package foreign: make: Entering directory `/cygdrive/g/rbuild/R-1.5.0/src/gnuwin32' make DLLNM= FLIBS="-lg2c -lRblas" BUILD=MINGW \ -C G:/Rbuild/R-1.5.0-recommended/R.INSTALL/foreign PKG=foreign

See if the following helps: > m <- outer(letters[1:5], 1:4, paste, sep="") > m [,1] [,2] [,3] [,4] [1,] "a1" "a2" "a3" "a4" [2,] "b1" "b2" "b3" "b4" [3,] "c1" "c2" "c3" "c4" [4,] "d1" "d2" "d3" "d4" [5,]

The cells are interpreted as counts, so by scaling you're analyzing a different experiment (one with fewer observations). So the chi-squared value will change (the terms (O-E)^2/E in the statistic scale linearly ignoring rounding and "Yates' continuity correction"). The chisq.test on the original data is a test of association. Conventionally you decide ahead of time on a

Hi, I've got the latest MIPS compilers that are C99 aware (7.4.4). "configure" finishes with: R is now configured for mips-sgi-irix6.5 Source directory: . Installation directory: /afs/bi/v/@sys/apps/stats/R/2.4.1 C compiler: cc -c99 -OPT:IEEE_NaN_inf=ON -g Fortran 77 compiler: f77 -OPT:IEEE_NaN_inf=ON -g C++ compiler: CC