similar to: ROC curve

Hi everybody, I am having a problem building a ROC curve with my data using the ROCR package. I have 10 lists of proteins such as attached (proteinlist.xls). each of the lists was calculated with a different p-value. The goal is to find the optimal p-value for the highest number of true positives as well as lowaest number of false positives. As far as I understood the explanations from the

Hi, i have a fairly large amount of genomic data. I have created a dataframe which has "Reference" as one column and "Variation" as another. I want to plot a ROC curve based on these 2 columns. I have serached the R manual but I could not understand. Can anybody help me with the R code for plotting ROC curve. Thnx ashu6886 -- View this message in context:

HI, Dear R community, My data set has 2409 variables, the last one is response variable. I have used the nnet after feature selection and works. But this time, I am using nnet to fit a model without feature selection. I got the following error information: > dim(train) [1] 1827 2409 nnet.fit<-nnet(as.factor(out) ~ ., data=train, size=3, rang=0.3, decay=5e-4, maxit=500) # model

sorry, I forgot my sessionInfo: please see below. -------- Original Message -------- Subject: puzzled with plotmath Date: Thu, 20 Jan 2011 12:48:18 +0100 From: Claudia Beleites <cbeleites at units.it> To: R Help <r-help at r-project.org> Dear all, I'm puzzled with matrix indices in plotmath. I'm plotting matrix elements: Z [i, i], and I'd like to put that as label.

Dear R users, Here is my problem: I have an array with at least four dimensions: > dim(myArray) [1] 20 17 3 6 I'd like to apply a function to each occurrence of the matrix (3x6) defined by the last two dimensions. This interpolation function always return a matrix of the same dimensions as its argument: > interpSecteurs.f(myArray[1, 1, , ]) secteur rotation 1 2 3

Hi R-Helpers , am working on nnet package.Multinom() has an option for finding the goodness of fit by giving the AIC value. Does nnet also gives some value to determine the accuracy. If not, can you guide me with some procedure to figure out the accuracy/goodness of fit of nnet model? Thanks in advance. -- View this message in context:

I'm attempting to sort a 3 dimensional array that looks like this > x , , 1 [,1] [,2] [1,] 9 9 [2,] 7 9 , , 2 [,1] [,2] [1,] 6 5 [2,] 4 6 , , 3 [,1] [,2] [1,] 2 1 [2,] 3 2 Such that it ends up like this .... > y , , 1 [,1] [,2] [1,] 2 1 [2,] 3 2 , , 2 [,1] [,2] [1,] 6 5 [2,] 4 6 , , 3 [,1] [,2]

Dear Group, I am looking for ways to use R and Matlab. Doing the data transformations in R and using the data in Matlab to analyze with some pre-defined scripts. Any good ways to transfer the data into matlab in its most recent version? I tried using R.matlab but the writeMat output is not readable by Matlab. I just need to output a data.frame and read it as is into matlab where I can do any

Dear List, I'm struggling with the signature writing cbind/rbind functions for a S4 class. First of all, I'm very happy that it is now possible to dispatch on ... I follow the example for "paste" in ?dotMethods, which works as far as this: ### start example setClass ("cbtest", representation = representation (data = "data.frame"),

> x <- train[,c( 2:18, 20:21, 24, 27:31)] > y <- train$out > > svm.pr <- svm(x, y, probability = TRUE, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) > > pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)], decision.values = TRUE, probability = TRUE) > attr(pred, "decision.values")[1:4,]

Dear all, I just noticed, that prompt () looses backticks that protect default arguments: f <- function (FUN = `*`) {} cat (prompt (f, NA)$usage) yields: \usage{ f(FUN = *) } %- maybe also 'usage' for other objects documented here. without the backticks, which is of course found by R CMD check as syntax error. While this is easily fixed if the .Rd is further edited manually, I

Dear List, a second, more general, question concerning S4 classes. I have a bunch of functions/methods for my class. At the moment I have them as methods, because they work on objects of my S4 class and therefore "belong" to that class. On the other hand, it is comparably unlikely that someone else wants the same kind of method. And package.skeleton () produces the

Hi I'm new to stats and R, so can you please help me or guide me building ROC curve in an elaborate way with codes I loaded ROCR package, but I'm not sure how to use it. Requirement To build ROC curve using only PSA(variable) alone of the original cohort against the ROC of the Model of the original cohort. It would be really great if you could help me with this. Thanks

Dear all, I work with (vibrational) spectra: some kind of intensity (I) over frequency (nu), wavelength or the like. I want to do fourier transform for interpolation, smoothing, etc. My problem is that the spectra are often irregularly spaced in nu: the difference between 2 neighbouring nu varies across the spectrum, and data points may be missing. Searching for discrete fourier transform

Dear all, I have trouble with R-beta sweaving files that include definitions with \SweaveInput in combination with keep.source = TRUE Symptom: SInput is taken from too far down the input file (the shift is the number of lines of the included file). Is that known? Searching didn't turn up anything, yet I think there are more people than just me using keep.source. Example: $

Dear R-Developers, could 'sample' gain a ... argument? As a convenience function, I added a sample Method to my hyperSpec class. This function however has a flag indicating whether the results should be returned directly as a hyperSpec object or rather as indices that give a random sample. For the moment, I use SetGeneric to add the dots argument, but this of course gives a warning

Hi, I understand for 1 d classifiers, you can use ROCR package. Is there a package you can plot ROC curve for 2d classifiers? One of my colleagues asked me about this. I have been quite puzzled, conceptually, how you can do the ROC curve for 2d classifiers. Can someone share his/her knowledge or experience? Thanks in advance. -- Waverley @ Palo Alto

Hi, I have the following question about creating data frames. I want to create a data frame with 2 components: a vector and a matrix. Let me use a simple example: y <- rnorm(10) x <- matrix(rnorm(150), nrow=10) Now if I do dd <- data.frame(x=x, y=y) I get a data frame with 16 colums, but if, according to the documentation, I do dd <- data.frame(x=I(x), y=y) then str(dd)

Dear all, I want to measure the goodness of prediction of my linear model. That's why I was thinking about the area under roc curve. I'm trying the following, but I don't know how to avoid the error. Any help would be appreciated. library(ROCR) model.lm <- lm(log(outcome)~log(v1)+log(v2)+factor1) pred<-predict(model.lm) pred<-prediction(as.numeric(pred),

Hi, I need to build ROC curve in R, can you please provide data steps / code or guide me through it. Thanks and Regards Rithesh M Mohan [[alternative HTML version deleted]]