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Can R support data manipulation programming that is available in the SAS datastep?  Specifically, can R support the following: -          Read multiple dataset one record at a time and compare values from each; then base on if-then logic write to multiple output files -          Load a lookup table and then process a different file; based on if-then logic, access and lookup values in the table

I have recently been using R - more speciifcally the GUI packages Rattle and Rcmdr. I like these products a lot and want to use them for some projects - the problem that I run into is when I start to try and run large datasets through them.  The data sets are 10-15 million in record quantity and usually have 15-30 fields (both numerical and categorical). I saw that there were some packages

Hola, Me gustaría obtener las reglas que genero con un árbol de decicisión creado con party. Algo parecido a lo que realiza esta función con rpart http://www.togaware.com/datamining/survivor/Convert_Tree.html la idea es disponer de esas reglas en un fichero de texto. En general si alguien sabe de algún paquete que permita obtener el código que genera la puntuación, el "score" para un

Hello, I''m a Java developer and I''m looking at Rails as a very interesting thing. I read the article http://theserverside.com/articles/article.tss?l=RailsHibernate and saw a couple of things that I didn''t like too much: 1) The N+1 problem This has been discussed in the thread (or should I say "flame"?) "Java people want to beat us". It seems

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Hi, . I know you can run Windows applications using WINE (winehq.com), but has anyone tried, say, running Word or Excel VBA code/macros based on Windows run time libraries? . the thing is that in their faq (http://www.winehq.com/site/docs/wine-faq/index) they don't even mention this possibility and searching on; VBA Word, doesn't give you any hits, even though WINE does link to windows

I have so far used the following command glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc + imf_pop + estbbo_m, family = binomial(link = "probit")) My question is 1. How do i discard the non significant selection variables (one out of the seven variables above is non-significant) and calculate the Inverse Mills Ratio of the significant variables 2. I need the inverse

For those haven''t seen it yet, Patrick Peak has an interesting article at the Server Side (www.theserverside.com) discussing the differences between the Hibernate (www.hibernate.org) peristence framework and ActiveRecord.  The article can be found here: http://www.theserverside.com/articles/article.tss?l=RailsHibernate .  Patrick Peak is the author of _Hibernate Quickly_ (Manning), which

I have an R file R_test.R saved in C:\R_test folder. The R_test.R looks like this: setwd("C:/R_test") rnorm(100) write(rnorm(100),"data.txt") q(save="no", runLast = F) Next I would like use an Excel VBA/macro Shell() function to call R and execute R_test.R file. The syntax is *Shell(pathname*[*,windowstyle*]*)* I wrote an Excel macro RunRcode like this: Sub

Look up ?try Regards Wayne -----Original Message----- From: pastaska1934 [mailto:pastaska1934@free.fr] Sent: 18 March 2004 14:36 To: R-help@stat.math.ethz.ch Subject: [R] don't stop when error occurs hi, i'm doing some bootstraping on a data set, using kmeans for each bootstrap, i mean i do a loop(200 times) and in each loop i use kmeans. i have to count some occurences in a matrix

Hello All, I'm having some trouble figuring out what the clearest way to plot my k-means clustering result on an my existing MDS. First I performed MDS on my distance matrix (note: I performed k-means on the MDS coordinates because applying a euclidean distance measure to my raw data would have been inappropriate) canto.MDS<-cmdscale(canto) I then figured out what would be my optimum

Hi there I have been using R to perform kmeans on a dataset. The data is fed in using read.table and then a matrix (x) is created i.e: [ mat <- matrix(0, nlevels(DF$V1), nlevels(DF$V2), dimnames = list(levels(DF$V1), levels(DF$V2))) mat[cbind(DF$V1, DF$V2)] <- DF$V3 This matrix is then taken and a distance matrix (y) created using dist() before performing the kmeans clustering. My query

Hi, I want to know which distance is using in the function kmeans and if we can change this distance. Indeed, in the function pam, we can put a distance matrix in parameter (by the line "pam<-pam(dist(matrixdata),k=7)" ) but we can't do it in the function kmeans, we have to put the matrix of data directly ... Thanks in advance, Nicolas BOUGET

On 19 February 2013 15:16, Arnold Schwaighofer <aschwaighofer at apple.com>wrote: > Do you have a base run with vectorization turned off? So we could see > where we are degrading things? > I wanted to, but after a few failed attempts, I couldn't pass the option to clang to disable vectorization. I don't want to make Galina reconfig the master every time, so I set up a

Hello. Is it possible to choose the distance in the kmeans algorithm? I have m vectors of n components and I want to cluster them using kmeans algorithm but I want to use the Mahalanobis distance or another distance. How can I do it in R? If I use kmeans, I have no option to choose the distance. Thanks in advance, Arnau.

SAS Enterprise Miner recommendeds to standardize using X / STDEV(X) versus [X ? mean(X)] / STDEV(X) Any thoughts on this? Pros Cons Philip

Hi All, I was using the following command for performing kmeans for Iris dataset. Kmeans_model<-kmeans(dataFrame[,c(1,2,3,4)],centers=3) This was giving proper results for me. But, in my application we generate the R commands dynamically and there was a requirement that the column names will be sent instead of column indices to the R commands.Hence, to incorporate this, i tried using the R

I was wondering if there was an R equivalent to the two phased approach that MATLAB uses in performing the Kmeans algorithm. If not is there away that I can determine if the kmeans in R and the kmeans in MATLAB are essentially giving me the same clustering information within a small amount of error? -- View this message in context:

Hi, I often work with R by writing long(ish) Excel-VBA macros interspersed with calls to R via RExcel. A typical example of this would be: Sub VBAMacro() 'fetch some data from an excel sheet 'do some basic stuff on said data 'transfer data from vba to R 'run some R statements 'get data back to vba 'show results on the excel sheet 'clean R by deleting all vars

Regarding a previous question concerning the kmeans function I've tried the same example and I also get a strange result (at least according to what is said in the help of the function kmeans). Apparently, the function is disregarding the initial cluster centers one gives it. According to the help of the function: centers: Either the number of clusters or a set of initial cluster