similar to: Is it possible to remove this loop? [SEC=UNCLASSIFIED]

Hi Tobias, Here is something I acquired from this mailing list some years ago. It works well for me: #---run in previous version (e.g. R 3.1.0) packages <- installed.packages()[,"Package"] save(packages, file="Rpackages_R3.1.0") #---run in new version load("Rpackages_R3.1.0") for (p in setdiff(packages, installed.packages()[,"Package"]))

Hi All, I installed R 2.5.1 recently on a PC (Windows XP Professional 2001) and tried to install some R packages. It took several minutes and gave me the following message. > utils:::menuInstallPkgs() --- Please select a CRAN mirror for use in this session --- Error in open.connection(file, "r") : unable to open connection In addition: Warning message: unable to connect to

Hi all, I used the following code and data to get auc values for two sets of predictions: library(caret) > table(predicted1, trainy) trainy hard soft 1 27 0 2 11 99 > aucRoc(roc(predicted1, trainy)) [1] 0.5 > table(predicted2, trainy) trainy hard soft 1 27 2 2 11 97 > aucRoc(roc(predicted2, trainy)) [1] 0.8451621 predicted1: 1 1 2

Dear All, I am currently using R in Windows PC with a 2 GB of RAM. Some pretty large datasets are expected soon, perhaps in an order of several GB. I am facing a similar situation like Ralph, either to get a new PC with a bigger RAM or else. I am just wondering if R is getting faster in other systems like UNIX or Linux. Any suggestions are appreciated. Regards, Jin

I am trying to multiply a 3D array of 4x4x4 by the 4 3D arrays of a 4D array with dimensions 4x4x4x4 (the last dimension being the one that I want to split by). (4x4x4 array) > hiaAry , , a1 i1 i2 i3 i4 h1 9.5936098 6.001040 0.08772 0.3138600 h2 1.2003500 1.454570 2.79248 0.0000000 h3 0.1346500 0.201220 0.39256 0.5464000 h4 0.0109000 0.012270 0.16417 0.2766900 ,

#I have a data set that looks like this. A bit more complicated actually with # three factor levels but these calculations need to be done on one factor at a #I then have a set of different rates that are applied #to it. #dataset cata <- c( 1,1,6,1,1,2) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) data1 <- data.frame(cata, catb, doga) rm(cata,catb,doga) data1 # start rates #

Dear Prof Ripley and Don, Thank you all for your kind reply. The UNIX system we have is Sparc Solaris v8 (a 64bit version). The Precompiled binary distributions of the base system and contributed packages are only available for Linux, MacOS X and Windows. The only thing available for UNIX seems Source Code for all Platforms. Could you please guide me to the "Prebuilt versions of R are

Hello R guru's I am a newbie to R, In my research work I usually generate a lot of ELISA data in form of absorbance values. I ususally use Excel to calculate the concentrations of unknown, but it is too tedious and manual especially when I have 100's of files to process. I would appreciate some help in creating a R script to do this with minimal manual input. s A1-G1 and A2-G2 are

Hi All, Just thought you might be interested in a recently released R package, spm: Spatial Predictive Modelling. It aims to introduce some novel, accurate, hybrid geostatistical and machine learning methods for spatial predictive modelling. Of 22 functions available in spm, two functions are for accuracy assessment. Perhaps they are not only useful tools for spatial predictive modelling

Hi All, I tried to use xgboost to model and predict count data. The predictions are however not as expected as shown below. # sponge count data in library(spm) library(spm) data(sponge) data(sponge.grid) names(sponge) [1] "easting" "northing" "sponge" "tpi3" "var7" "entro7" "bs34" "bs11"

Hello there I have the following model based on the hollings disc equation for the type II functional response for 2 data sets: nls(eaten~(a*suppl)/(1+a*h*suppl) where eaten is the number of prey eaten by a predator and suppl is the number of prey initially supplied to the same predator. I have parameter estimates of 'a' and 'h' for the two populations studied and would like

Hello, I've been working with "nnet" and now I'd like to use the weigths, from the fitted model, to iterpret some of variables impornatce. I used the following command: mts <- nnet(y=Y,x=X,size =4, rang = 0.1, decay = 5e-4, maxit = 5000,linout=TRUE) X is (m x n) Y is (m x 1) And then I get the coeficients by: Wts<-coef(mts) b->h1 i1->h1

I don't know why, but for my case, I reduced the tinc topology from a complex one(which provide layered redundancy) to a very simpled one(one connection), and that connection drop disappeared. Later, let me draw the topology and share the config to you to see if there's any findings of the cause. Guus Sliepen <guus at tinc-vpn.org>于2017年9月14日 周四上午3:20写道： > On Wed, Sep 13, 2017

Hello, I'm trying to calculate a certain distance estimator for my thesis. I have a program in C that works fine when I call it with .C() in R, but since I'm dealing with big matrices like 30000x20000 it was getting a stack overflow. Now I have the same program but more efficeintly coded using malloc, and it works perfectlry in C, compiles well with R CMD SHLIB but when I call it with

Hi, I have two KVM host: h1 and h2, both of them mount an NFS directory as a shared storage. I can save (virsh save <domain> <file>) a domain in h1 to a state file in the shared storage successfully, but failed to restore it from h2 with the following error message: # virsh restore testRes.dat error: Failed to restore domain from testRes.dat error: operation failed: failed to start VM

Hi All This is a general stats problem that I am dealing with using R, so any help is greater appreciated. I have two lognormal distributions with means M1 and M2. If we have: H0: log(M1/M2)=0 H1: log(M1/M2) !=0 equivalent to log(M1/M2)=log(1+P) where P<0 or P>0. If we calculate the power for a value of P=0.1 or P=-0.1 (i.e. a 10% difference) and say assume SE{log(M1/M2)}=0.05, and

Hi, I am computing the Nelson-Aalen (NA) estimate of baseline cumulative hazard in two different ways using the "survival" package. I am expecting that they should be identical. However, they are not. Their difference is a monotonically increasing with time. This difference is probably not large to make any impact in the application, but is annoyingly non-trivial for me to just

Hi, I'm having trouble within my function CalcPos to get it to call CalcHorz with values from each row. I *think* it's calling CalcHorz with the final values of the inputs and not the values from each row. How can I do this properly in R? The values aa,bb,cc,dd are inputs. CalcPos first calculates V1 and V2 vertically, and then I attempt to call CalcHorz to handle H1, H2 & H3

Hi, Am working on neural network. Below is the coding and the output > library (nnet) > uplift.nn<-nnet (PVU~ConsumerValue+Duration+PromoVolShare,y,size=3) # weights: 16 initial value 4068.052704 final value 3434.194253 converged > summary (uplift.nn) a 3-3-1 network with 16 weights options were - b->h1 i1->h1 i2->h1 i3->h1 16.64 6.62 149.93

Hi folks, here is a short RFC regarding hashing for the implementation of switch statements and my preliminary patch. I posted this patch on 2014-01-16 21:58 at llvm-commits at cs.uiuc.edu. You can find a copy e.g. on http://lists.cs.uiuc.edu/pipermail/llvm-commits/Week-of-Mon-20140113/201782.html. Best regards Jasper === Preliminary: Special identifiers n number of given switch labels