similar to: Missing data problem and ROC curves

Hello I am trying to make a graph of 10 different lines built each from 4 different segments and to add a darker line that will represent the average of all graphs - all in the same plot.Actually each line is a ROC plot The code I'm using for plotting one line is as follows: logit.roc.plot <- function(r, title="ROC curve") { old.par <- par(no.readonly = TRUE);

Hello I am trying to make a graph of 10 different lines built each from 4 different segments and to add a darker line that will represent the average of all graphs - all in the same plot.Actually each line is a ROC plot The code I'm using for plotting one line is as follows: logit.roc.plot <- function(r, title="ROC curve") { old.par <- par(no.readonly = TRUE);

Back on 18-June a colleague (Earl Glynn) asked: ================== I did a ?package.contents in version 1.9.0. The help file says this is deprecated, and says to "see also" Deprecated and Defunct, but what is the "new" function that replaces packge.contents? The function still seems to work, but it's just tagged as deprecated. efg ================== I have the

I have found a quite strange (to me) behaviour in Sweave. It only occurs in the following situation: 1. define a variable in one chunk 2. use it within a subsequent figure-generating chunk 3. delete it at the end of that same chunk Then the Sweave driver chokes, not finding the variable name when generating the figure Example: % document bug2.Rnw \documentclass{article} \usepackage{Sweave}

I am sure there is something simple here I am missing, so please bear with me. It concerns the computation of the confidence interval for a population mean. The data are 125 measurements of Cs137 radation, a sample data set from Davis "Statistics and Data Analysis in Geology" 3rd ed. (CROATRAD.TXT) ------------------ method 1: using textbook definitions: mean \pm se_mean * t-value mu

Hi, I'm trying to set up a prediction software, now i testing the performance of my method, so i need to calculate a ROC curve, specially auc, cut-off, sens and spec, i just looking at ROCH package, but it's a mass for me, i'm not a math guy and I'm getting lost Could any of you recommend me an easy-to-use package to do this task? i just have a list of positive/negative samples

Hello, I am afraid I do not fully understand all intricacies of programming in lattice plots. In the code below I try to plot an ROC curve, following R-news 4(1). When I condition on the variable 'group' I get the error message below, when I plot the curve for all data (i.e., y ~ pred.prob), I get the plot I want. Can someone point out why conditioning gives that message? Thanks, Ruud

Dear Guru's, Is there a package (R of course) with programs for diagnostics - roc, sens , spec, kappa etc? Best wishes Fredrik L

Dear all, I get a strange error when I find polychoric correlations with the ML method, which I have been able to reproduce using randomly-generated data. What is wrong? I realize that the data that I generated randomly is a bit strange, but it is the only way that I duplicate the error message. > n<-100 > test.x<-rnorm(n, mean=0, sd=1) > test.c<-test.x + rnorm(n, mean=0,

hi i have gone through the achieves but still could not get my bridge to suvive a reboot . please can anyone help me am using fedora core 2 -----Original message----- From: bridge-request@lists.osdl.org Date: Fri, 28 Jan 2005 03:08:06 +0100 To: bridge@lists.osdl.org Subject: Bridge Digest, Vol 17, Issue 25 > Send Bridge mailing list submissions to > bridge@lists.osdl.org > >

Hola! Tengo que hacer una curva ROC com unos datos que obtuve de hacer una macro de excel y aplicar unas reglas, y basicamente tengo que a partir de la variacion del tiempo y la velocidad del barco obtengo diferentes porcentajes de true positives (TP) y false positives (FP) y con eso deberia de construir una curva ROC. Dada mi ignorância en este tema, no se muy bien por donde empezar , estuve

Hi: I have encountered problems with imodwt and universal.thresh.modwt and cannot find any reference in R Search. Hope someone can give me some ideas: Starting with modwt.la8 <- modwt(xdata, "la8", n.level=6) <-- this seems to work fine (1) ydata <- imodwt(modwt.la8) will always give ydata as numeric(0) (no values) instead of being a time series data with

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

Dear R users, pROC is a package to compare, visualize, and smooth receiver operating characteristic (ROC) curves. The package provides the following features: * Partial or full area under the curve (AUC) computation * Comparison of two ROC curves (curves and AUC) * Calculating and plotting confidence intervals * Smoothing of the ROC curve * Coordinates extraction ('coords' function).

Dear R users, pROC is a package to compare, visualize, and smooth receiver operating characteristic (ROC) curves. The package provides the following features: * Partial or full area under the curve (AUC) computation * Comparison of two ROC curves (curves and AUC) * Calculating and plotting confidence intervals * Smoothing of the ROC curve * Coordinates extraction ('coords' function).

Hi, Dear all R users: Does someone know whether R can calculate the Receiver Operating Characteristic (ROC) Curves? I didn't find it from the packages. Thanks a lot. --- Xin

Hi, Is there any package or code to compare and display correlated ROC curves in R? Thanks, Reza [[alternative HTML version deleted]]

At useR 2006 I mentioned that it would be nice to have a way to specify binomial links that involved free parameters and described some experience with a Gosset link involving a free degrees of freedom parameter, and a Tukey-lambda link with two free parameters. My implementation of this involved some rather kludgey modifications of binomial, make.link and glm that (essentially) added a

Dear all, I am looking for an R package that allows me to calculate and plot the confidence intervals for the roc curve using for example some bootstrapping. I tried "ROCR" who seems doing such work but i couldn't find the right option in it. Many thanks Bests Marc _________________________________________________________________ [[alternative HTML version deleted]]

Hallo! Does anybody know a way to calculate the sample size for comparing AUC of ROC curves against 'by chance' with AUC=0.5 (and/or against anothe AUC)? Thanks! Karl