similar to: efficient rolling rank

I have pretty big data sizes, like matrices of .5 to 1.5GB so once i need to juggle several of them i am in need of disk cache. I am trying to use bigmemory package but getting problems that are hard to understand. I am getting seg faults and machine just hanging. I work by the way on Red Hat Linux, 64 bit R version 10. Simplest problem is just saving matrices. When i do something like

Hi, i have 8.10 Ubuntu, R version 2.7.1 on 64 bit pc. I install packages fine, but when i try to do install.packages("debug") i get error message package 'debug' is not available Does this package exist for Ubuntu? -- View this message in context: http://n4.nabble.com/package-debug-not-available-in-Ubuntu-tp1597844p1597844.html Sent from the R help mailing list archive at

I would like to make a ranking operation more efficient if possible. The goal is to rank a set of points representing objective function values such that points which are "dominated" by no others have rank 1, those which are dominated by one other point have rank 2, etc. In the example with two dimensions below, objective functions 1 and 2 are to be minimized. Points a-e are

Hi, I'm wondering if anyone can point me to a function that will allow me to do a ranking that treats ties differently than rank() provides for? I'd like a method that will assign to the elements of each tie group the largest rank. An example: For the vector 'v', I'd like the method to return 'rv' v: 1 2 3 3 3 4 5 5 6 7 rv: 1 2 5 5 5 6 8 8 9 10 Thanks,

Hello, What is the best way to get ranks for a vector of values, limit the range of rank values and create equal count in each group? I call this uniform ranking...uniform count/number in each group. Here is an example using three groups: Say I have values: x = c(3, 2, -3, 1, 0, 5, 10, 30, -1, 4) names(x) = letters[1:10] > x a b c d e f g h i j 3 2 -3 1 0 5 10 30 -1 4 I

Dear R-developers, I just realized that rank() behaves inconsistent if combining one of na.last in {TRUE|FALSE} with a ties.method in {"average"|"random"|"max"|"min"}. The documentation suggests that e.g. with na.last=TRUE NAs are treated like the last (=highest) value, which obviously is not the case: > rank(c(1,2,2,NA,NA), na.last = TRUE, ties.method

Hi R users, My goal is to rank my samples according to how they fall out in a histogram with 10 bins to produce a ranking for each sample according to where it falls on the histogram, with a "1" to represent one tail of the hist, a "10" to represent the other tail, and a "5" for the median/mean. I have a number of different data sets to do this with and in all cases

Hi, I'm using package "caret" to rank predictors using random forest model and draw predictors importance plot. I used below commands: rf.fit<-randomForest(x,y,ntree=500,importance=TRUE) ## "x" is matrix whose columns are predictors, "y" is a binary resonse vector ## Then I got the ranked predictors by ranking

Hello All: I have a vector of data, z > z [1] 0.1 0.1 0.1 0.1 0.2 0.2 0.3 0.3 0.3 0.4 0.5 0.5 0.5 0.7 0.7 0.7 0.9 0.9 1.1 [20] 1.1 1.2 1.3 1.4 The first 4 elements have values of 0.1 followed 2 elements with values 0.2. When I invoke rank(z), I expected to get (1+2+3+4)/4 = 2.5 for the first 4 elements in the ranking and (5+6)/2 = 5.5 for elements 5 and 6. But what I do

Hi all, I am a biostatistician and I have developed my own ranking system for clinical data. I would like to test the efficiency of it w.r.t. to other ranking systems. I would like to simulate the data and after assigning ranks to my observed scores(after neglecting dropouts), observe the type I error. If I want to do a Kruuskal Wallis type of test, what test statistic should I use to test for a

Hello, I would like to work with Orange as part of GSoC 2012(and continue henceforth). Apologies for joining in a bit late- i was waiting to get a proper grasp of things before discussing it here. Currently I am a Masters students in Mathematics with my bachelors in Computer Science[integrated dual degree]. Over the last year and a half, I have worked on a few ML projects and have a couple of

Full_Name: Doug Grove Version: R.1.9.1 OS: Linux Submission from: (NULL) (140.107.156.61) I just found that rank() has a 'decreasing' argument that is not documented in its help page. I checked my version of 2.0.0 (original release hence unpatched) and it is not documented there. For curiousity I also went back to version 1.8.1 and checked the function (not the documentation)and at

I have a question concerning the Wilcoxon signed-rank test, and specifically, which R subroutine I should use for my particular dataset. There are three different commands in R (that I'm aware of) that calculate the Wilcoxon signed-rank test; wilcox.test, wilcox.exact, and wilcoxsign_test. When I run the three commands on the same dataset, I get different p-values. I'm hoping that

Hello, I am Mudit Raj Gupta, fourth year student of M.S. (Hons.) Chemistry and B.E. (Hons.) Electronics and Instrumentation at BITS-Pilani ( http://www.bits-pilani.ac.in/). I am interested in *Machine Learning and Computaional Intelligence*. I have an interest in implementing various existing algorithms and developing modified/new algorithms related to machine learning and computational

Hi all, I am using ACS micro data (PUMS) with one of the columns as a factor for the place of birth (POBPF). I would like to create a column (POBR) containing a rank corresponding to the place of the observation in the POBPF rankings. For example, if a person is from Oregon, Oregon is the most popular Place of Birth, so each person who came from Oregon should have a 1 in their POBR.

Dear Sir, I am Pankaj Singhal from Jaipur, India. I am very much interested and strongly looking forward in getting involved in this project Learning-to-Rank. My previous experience in this field is good. Last semester I did a similar job of ranking the URLs of the given huge dataset based on their attribute values. The dataset consisted hundreds of thousands of URLs and each url

Hello all, This is in reference to "Learning to Rank" Project Idea. [I know, i made the entry a bit late, but hope you are still in interest to help out] I am looking for suggestions to help me narrowing down the choices of algorithms. I had been readily surveying on the referred algorithms for the purpose of choosing the right one. I am mentioning here some of my doubts to discuss and

I have not been able to find a way to do dense rank in R Here is an example of what I need rank() gives the following 5 rank 1 7 rank 2 7 rank 2 9 *rank 4* but I want 5 rank 1 7 rank 2 7 rank 2 9 *rank 3* * * thanks SS [[alternative HTML version deleted]]

SAS proc rank has ties options of high and low that would allow producing ranks of the type found in the sports pages, e.g., rank (c(1,1,2,2,2,2,3)) == 1 1 3 3 3 3 7 Could R support these ties.methods?

Hello everyone, I am Abhiroop, 3rd year engineering student from BITS Pilani, India. I was going through the idea list of Xapian Search Engine Library and the idea Learning to Rank interested me. I am not very well conversant with C++. However I have done a lot of development work in Java and Python. And i have done a project in C# too. Currently I am working on 2 projects: 1.Distributed Data