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Dear all, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

Dear all I am trying to compare the performances of several methods using the AUC0.1 and not the whole AUC. (meaning I wanted to compare to AUC's whose x axis only goes to 0.1 not 1) I came to know about the Mcneil Hanley test from Bernardo Rangel Tura and I referred to the original paper for the calculation of "r" which is an argument of the function cROC. I can only find the

I might be missing something but I thought that AUC was a measure for comparing ROC curves, so there is nothing else needed to "compare" them. The larger AUC is the higher correlation of 2 variables compared. No other measures or calculations are needed. Jarek Tuszynski -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On

Please help. I found the code in the archive. The author of this script says: "The first function (seROC) calculate the standard error of ROC curve, the second function (cROC) compare ROC curves." Can some one explain to me what are the na, nn and r parameters which are used as the input to the following two functions? Thanks much in advance. > From: Bernardo Rangel Tura >

Hi, I am quite new to R and I have two questions regarding ROCR. 1. I have tried to understand how to extract area-under-curve value by looking at the ROCR document and googling. Still I am not sure if I am doing the right thing. Here is my code, is "auc1" the auc value? " pred1 <- prediction(resp1,label1) perf1 <- performance(pred1,"tpr","fpr") plot(

Guys, I used Random Forest with a couple of data sets I had to predict for binary response. In all the cases, the AUC of the training set is coming to be 1. Is this always the case with random forests? Can someone please clarify this? I have given a simple example, first using logistic regression and then using random forests to explain the problem. AUC of the random forest is coming out to be

Hi, I recently bought a Nitram Elite 2005 UPS and i installed nut to monitor it. Unfortunatly, i often have timeout errors (20 timeout per days): Broadcast Message from aurelien at berkelium (no tty) at 18:05 CET... Communications with UPS Nitram at localhost lost Broadcast Message from aurelien at berkelium (no tty) at 18:05 CET... Communications with UPS Nitram(AT)localhost

Hi, I recently bought a Nitram Elite 2005 UPS and i installed nut to monitor it. Unfortunatly, i often have timeout errors (20 timeout per days): Broadcast Message from aurelien at berkelium (no tty) at 18:05 CET... Communications with UPS Nitram at localhost lost Broadcast Message from aurelien at berkelium (no tty) at 18:05 CET... Communications with UPS Nitram(AT)localhost

Dear sirs, I have tried to find a command to fit(plot) a regression line but I haven't found any command on the html.help. My question is if I am using a regression for instance reg<-lm(y~x) and I would like to make a regression line, to see how well my data is fit. Can you please help me with this?? Yours Sincerely Soheila Zad

Hi everybody, I recently bought a UPS Cyber Power DX600E ad I'm trying to manage it through Nut under FreeBSD. Unfortunately, usbhid-ups returns an error when I do: [root at berkelium /usr/local/etc/nut]# /usr/local/libexec/nut/usbhid-ups -u root -DD -a onduleur Network UPS Tools - Generic HID driver 0.34 (2.4.1) USB communication driver 0.31 debug level is '2'

I am a novice user of R and am stumbling on how to order a dataset produced during my session. I have a 1863 row X 14 column dataset that I want to put out to a file. I want the output sorted by the first column and then by the second column both in ascending order. The first column is character and the second is numeric (I hope). I used an "as.numeric" function to assign that

Here is a snippet to show what i'm trying to do. library(randomForest) library(ROCR) library(caret) data(iris) iris <- iris[(iris$Species != "setosa"),] fit <- randomForest(factor(Species) ~ ., data=iris, ntree=50) train.predict <- predict(fit,iris,type="prob")[,2]

My guess is `area under the ROC curve'. There's the roc package in BioConductor that I believe can compute this. Andy > From: Spencer Graves > > What's AUC? If you mean AIC (Akaike Information > Criterion), and > if you fit logistic regression using "glm", the help file > says that glm > returns an object of class "glm", which is

Pleased to announce that the next version (2.3.0) of our package ?concurve? is out on CRAN (https://cran.r-project.org/package=concurve). In addition to plotting confidence (consonance) curves, it can now plot two functions next to one another to see the amount of overlap. It can also plot likelihood and deviance functions along with consonance densities and distributions. And it can utilize

Pleased to announce that the next version (2.3.0) of our package ?concurve? is out on CRAN (https://cran.r-project.org/package=concurve). In addition to plotting confidence (consonance) curves, it can now plot two functions next to one another to see the amount of overlap. It can also plot likelihood and deviance functions along with consonance densities and distributions. And it can utilize

The Wine maintenance release 5.0.1 is now available. What's new in this release (see below for details): - Fix compilation with gcc 10 - Add some timezones - Various bug fixes The source is available from the following locations: https://dl.winehq.org/wine/source/5.0/wine-5.0.1.tar.xz http://mirrors.ibiblio.org/wine/source/5.0/wine-5.0.1.tar.xz Binary packages for various

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Hallo all, I have the following glm model: f1 <- as.formula(paste("factor(y.fondi)~", "flgsess + segmeta2 + udm + zona.geo + ultimo.prod.", "+flg.a2 + flg.d.na2 + flg.v2 + flg.cc2", " +(flg.a1 + flg.d.na1 + flg.v1 + flg.cc1)^2", " + flg.a2:flg.d.na2 + flg.a2:flg.v2 +

Dear R-Core, after switching to 2.3.0, all my trusted do.call constructs that worked in 2.2 and earlier fail. I noted that changes were introduced to do.call, but I could not find out how these relate to my problem. The following example works in 2.2 and earlier, but fails because rownames are partially NA. I can correct this by manually adding row names, but it's a bit of work to check this

Dear all, I want to compute the average of the three blocks for each x-variable which is equal slide in the code below. How can I do that ? block x1 x2 x3 x4 x5 1 23 22 23 24 23 1 21 25 26 21 39 1 23 24 22 23 23 2 20 21 23 24 28 2 32 23 34 24 26 2 19