similar to: rpart help

Hello All, Has anyone had success building 64-bit R on Solaris 10 Sparc with the Oracle Studio Compiler suite? Could anyone start give me a clue. I have tried to no avail. Thanks, Nynese Nynese Tinsley, BSEE, MSCIS UNIX Systems Analyst Harvard School of Public Health Center for Biostatistics in AIDS Research 651 Huntington Ave, FXB 614 Boston, MA 02115 617-432-3244 office#

Hello R Help, I am attempting to install/build a 64-bit version of R to hopefully resolve some memory.limit problems for a user who is running a simulation. The 'configure' runs fine and the compilation (make) runs fine until the very last part (see below). I have libiconv in /usr/local/lib (no sure why I am getting the referencing error). The config.site file is attached. ANY HELP YOU

Hi, Are there some packages which can generate multi-normal, multi-t, etc multivariate sampling? thanks! Best wishes, Peng ******************************* Peng Zhang Department of Biostatistics Harvard School of Public Health 655 Huntington Avenue Boston, Massachusetts 02115 ******************************* I believe I can fly I believe I can touch the sky

Hi Thanks for replying my question! What really interested me is that the package providing some complex form sampling, such as wishart, multinomial, dirichlet. And others for example conditional beta distribution confining the random variable in the interval (a, b). Since these concept are widely used in the baysian, I wonder whether somebody has already written this package. Thanks! Best

Dear R-users, I'm working with the Rpart package and trying to understand how the procedure select the best split in the case the method "class" and the splitting index "Gini" are used. In particular I'd like to have look to the source code that works out the best split for un unordered predictor. Does anyone can suggest me which functions in the sources I should

Greetings, I'm having a problem with something that I think is very simple - I'd like to be able to use the 'sapply' and 'by' functions in 1 function to be able (for example) to get regression coefficients from multiple models by a grouping variable. I think that I'm missing something that is probably obvious to experienced users. Here's a simple (trivial)

Hello there, I just changed to FreeBSD platform, and want to install R on it. I use FreeBSD 5.0 and install nearly all packages on the machine. When I use ports to install R, (cd /usr/ports/math/R-letter, and then type make) I got the following error information. ../../../../library/methods/libs/methods.so is unchanged dumping R code in package 'methods' Fatal error: The X11 shared

Dear R users, I'm working with the rpart package and want to evaluate the performance of user defined split functions. I have some problems in understanding the meaning of the xval argument in the two functions rpart.control and xpred.rpart. In the former it is defined as the number of cross-validations while in the latter it is defined as the number of cross-validation groups. If I am

Dear all, I'm writing my own method to be used in Rpart by defining the list of functions named init, split and eval. I'm following the example given in the file 'tests/usersplits.R' in the sources. By now I'm able to define the split function (and it works correctly in the tree construction) while I have some problems with the init and the eval function. The task I'm

Dear R users, I know cross-validation does not work in rpart with user defined split functions. As Terry Therneau suggested, one can use the xpred.rpart function and then summarize the matrix of the predicted values into a single "goodness" value. I need only a confirmation: set for example xval=10, if I correctly understood a single column of the matrix obatined by xpred.rpart gives

When I run the gam function as part of an optimization and do the optimization many times using a loop, I'm finding that memory use increases over time (based on simply monitoring top). Below is some example code that involves varying the penalty parameter in gam, trying to find the value that gives exactly 50 edf for a simple smoothing problem. I thought I would post to the list to see if

Good Afternoon R Help! On of my users is seriously thinking about moving to R from Splus. In his testing, he has already found some benefits to it. He has, however run into one issue, calling his Fortran functions in R. Previously, in Splus, he would do the following: 1. Compile via f90 the *.f program 2. link the object file to the Fortran IMSL libraries via the 'ld' command 3.

Hi, I'm trying to follow the R-admin instructions for using MKL10 as the external BLAS compiling R-2.6.2 under Linux on a RH EL head node of a cluster. The configure process seems to have problems when it checks for dgemm in the BLAS. I'm using configure as: ./configure CC=icc F77=ifort --with-lapack="$MKL" --with-blas="$MKL" where $MKL is defined as in R-admin

Greetings, Does anyone know how to get an id number in the little header above each individual plot within a trellis plot? The default seems to be to print the word id and add a line indicating on a linear scale where the current id sits. Thanks in advance for any help you can send, Suzette ================================= Suzette Blanchard, Ph.D. Research Scientist Frontier Science

Hello there. I have fitted a rpart model. > rpartModel <- rpart(y~., data=data.frame(y=y,x=x),method="class", ....) and can use rpart$where to find out the terminal nodes that each observations belongs. Now, I have a set of new data and used predict.rpart which seems to give only the predicted value with no information similar to rpart$where. May I know how

Hi, I am new to R and need help with rpart. I am trying to create a classification tree using rpart. In order to plot the reults I use the plot function and the text function to label the plot of the tree dendrogram with text. The documentation of text.rpart says : "For the "class" method, label="yval" results in the factor levels being used, "yprob" results

Hi all, I am very new to R (only two days of studies). I know a little bit of statistical learning and looking for an implementation of CART and random forest and therefore I am now studying R. I tested with rpart and randomForest package, they are quite good. However, I need a classification tree and for each training data, there is different loss. (i.e. the loss function is not purely 0-1,

Greetings - Is there a way to automatically perform what I believe is called "rule extraction" (by Quinlan and the machine learning community at least) for the leaves of trees generated by rpart? I can use path.rpart() to automatically extract the paths to the leaves, but these can be needlessly cumbersome. For example, one path returned by path.rpart() might be: [1]

After fitting and pruning an rpart model, it is often the case that one or more of the original predictors is not used by any of the splits of the final tree. It seems logical, therefore, that values for these "unused" predictors would not be needed for prediction. But when predict() is called on such models, all predictors seem to be required. Why is that, and can it be easily

I have created plots of rpart objects with the fancy option for text.rpart ("fancy" creates ellipses and rectangles and labels branches with splitting criteria). The ellipses and rectangles are supposed to "interrupt" the tree lines (as seen in Therneau and Atkinson 1997, page 48, Fig. 18, http://www.mayo.edu/hsr/techrpt/61.pdf), but they do not, even when I use Therneau and