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I have a 64-bit windows box - Intel Xeon CPU E7340 @ 2.4GHz 31.9GB of RAM I have R 2.11.1 (64bit) running on it. My csv data is 3.6 GB (with about 15 million obs, 120 variables.) ------------------------------------------------ I have successfully imported the data above into R. No problem. Now I am trying to run 'rpart' on my data. But I got the following error : Error: cannot

I have a one-variable data set in R. The plot of histogram of my numerical variable suggests an inverse gaussian distribution. How can I obtain best estimation for the two parameters of inverse gaussian based on my data? Thanks. -- View this message in context: http://n4.nabble.com/estimate-inverse-gaussian-in-R-tp949692p949692.html Sent from the R help mailing list archive at Nabble.com.

I have found an existing image on Amazon EC2 including R. But unfortunately, it is 32-bit R on 32-bit Linux. Does anybody know if there exists an mage (R 64-bit on Linux 64-bit) on Amazon EC2? Or how can I install 64-bit R on my own Linux instance there? Thanks. -- View this message in context:

Have anybody used Decision Tree in Python or C++? (or written their own decision tree implementation in Python or C++)? My goal is to run decision tree on 8 million obs as training set and score 7 million in test set. I am testing 'rpart' package on a 64-bit-Linux + 64-bit-R environment. But it seems that rpart is either not stable or running out of memory very quickly. (Is it

Currently, we have developed an R package for our company's internal use (at least for now). I have successfully built the package and generated zip file which can be easily installed. However, I am not sure how to generate the big HELP file in PDF. Right now, I have about 30+ Rd files for this internal package. I can run 'R CMD Rd2dvi' and WinEdt to create one pdf file

R version 2.8.1 (2008-12-22) on Linux 64-bit I am trying to run 'rulefit' function (Rule based Learning Ensembles). but I got the following error - > rulefit(x,y) Warning: This program is an suid-root program or is being run by the root user. The full text of the error or warning message cannot be safely formatted in this environment. You may get a more descriptive message by running

I think that I have successfully installed libreadline.so.6. But still got an error -- libreadline.so.6 needed during R installation on SUSE Linux. help is really appreciated! =============================== # ls -lt /usr/local/lib total 4088 -rw-r--r-- 1 root root 168858 Oct 18 07:15 libhistory.a lrwxrwxrwx 1 root root 15 Oct 18 07:15 libhistory.so -> libhistory.so.6 lrwxrwxrwx 1

I am trying to install 64 bit R on Linux. But I got the following error - rpm -i R-core-2.10.0-2.fc11.x86_64.rpm warning: R-core-2.10.0-2.fc11.x86_64.rpm: Header V3 DSA signature: NOKEY, key ID 97d3544e error: Failed dependencies: /bin/bash is needed by R-core-2.10.0-2.fc11.x86_64 /bin/sh is needed by R-core-2.10.0-2.fc11.x86_64 /sbin/ldconfig is needed by

I am trying to install R on Linux (Redhat 4). But 'yum' does not seem to work... thanks for your help/hints/suggestions in advance! ------------ $ sudo cat /proc/version Linux version 2.6.34.6-54.24.amzn1.i686 (mockbuild at build-31003.build) (gcc version 4.1.2 20080704 (Red Hat 4.1.2-48)) #1 SMP Fri Sep 17 23:13:59 UTC 2010 $ sudo yum install

I am reading the Mining of Massive Datasets Book by Rajaraman and Ullman. It has a good explanation of Recommendation System at Chapter 9. But what are the relationship between 1) SVD (Singular Decomposition) 2) UV-Decomposition 3) NMF (Non-negative Matrix Factorization) In particular, it seems 2) and 3) can be very similar. Is it right? Thanks. -- View this message in context:

I am trying to figure out why 'biglm' can handle large data set... According to the R document - "biglm creates a linear model object that uses only p^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory." After reading the source code below? I still could not figure out how 'update'