similar to: Error in conditional execution "missing value where TRUE/FALSE needed"

Hello R friends, I want to use my R script in VB to make macro in Excel. I tried with RExcel but it seems to me that this package is just GUI API and I still have to run(connect) R to use the script. Google tells me there are some ways to make R script as an independent library/module/header so that I can call it in VB, C or JAVA. Where can I get detailed tutorial or manual for that? Thanks in

Hello thankful R friends, Can I use iteration (for) or conditional (if) syntax in rexcel using rrun? I've finished coding my program and want to run through Excel. I just want to run such as Call rinterface.RRun("for(i in 1:10){") Call rinterface.RRun("a[i,1]<-i") Call rinterface.RRun("}") But it doesn't work. Any solution or trick to use "for"

The name conflicts in Epi and ROC packages (2 'ROC' functions are the problem) cause the following code to work once, but not twice: library(MASS); data(cats); x = cats[,2] y = ifelse(cats[,1]=='F',0,1) library(Epi); ROC(x,y,grid=0)$AUC library(ROC); AUC(rocdemo.sca(y, x, dxrule.sca)) What is the standard way of resolving name conflicts? Ask maintainers to resolve

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);

Dear all, Some functions like 'ROC(Epi)' can be used to perform ROC analyssi, but it needs us to specify the fitting model in the argument. Now i have got the predicted p-values (0,1) for the 0/1 response variable using some other approach, see the following example dataset: id mark predict.pvalue 1 1 0.927 2 0 0.928 3 1 0.928 ..................

Dearh all, I have following question: a script (using pROC functions) that works when run in Rgui, failes when run through rscript. This is the script: library(pROC) hits <- c("T", "D", "T", "D", "T", "D", "T", "D", "T", "D", "T", "D", "T", "D",

*Dear Bert, * Thank you very much for your feedback and the useful link https://rseek.org/ and https://www.r-bloggers.com/calculating-auc-the-area-under-a-roc-curve/. Actually, I want to know different performance between Stata and R, in multilevel logistic regression. For this purposes, I replicate ".do" file use Stata in

Hi, I was lately debugging parts of my 'colAUC' function in caTools package, and in a process looked into other packages for calculating Areas Under ROC Curves (AUC). To my surprise I found at least 6 other functions: * wilcox.test * AUC from ROC package, * performance from ROCR package, * auROC from limma package, * ROC from Epi package, * roc.area from verification

Hello I am new in R. I am trying to implement Biomod 2 package. However, I have a doubt. I want to calculate the mean and sd of "Testing.data" (ROC and TSS) > # let's print the ROC scores of all selected models > myBiomodModelEval_55["ROC","Testing.data",,,] RUN1 RUN2 RUN3 RUN4 RUN5 RUN6 RUN7 RUN8 RUN9 RUN10 0.938 0.938 0.926 0.931 0.939

Hi, I was trying to draw some ROC curves (prediction of case/control status), but seem to be getting a somewhat jagged plot. Can I do something that would 'smooth' it somewhat? Most roc curves seem to have many incremental changes (in x and y directions), but my plot only has 4 or 5 steps even though there are 22 data points. Should I be doing something differently? How can I provide a

I have the same problem of a previous request HOW to use the survivalROC (or another library in R) to get optimal cut-off values? I want to use the time-dependent survivalROC package.according to the,reference material,it only gives a partial set of ordered cut-off values .eg. -------------------------------------------------------------------------------- data(mayo) str(mayo) attach(mayo)

Dear R-philes, I am plotting ROC curves for several cross-validation runs of a classifier (using the function below). In addition to the average AUC, I am interested in obtaining a confidence interval for the average AUC. Is there a straightforward way to do this via the ROCR package? plot_roc_curve <- function(roc.dat, plt.title) { #print(str(vowel.ROC)) pred <-

> On Jun 26, 2017, at 11:40 AM, Brian Smith <bsmith030465 at gmail.com> wrote: > > Hi, > > I was trying to draw some ROC curves (prediction of case/control status), > but seem to be getting a somewhat jagged plot. Can I do something that > would 'smooth' it somewhat? Most roc curves seem to have many incremental > changes (in x and y directions), but my plot

I have the same problem of a prevous request HOW to use the survivalROC (or another library in R) to get optimal cut-off values? I want to use the time-dependent survivalROC package.according to the,reference material,it only gives a set of ordered cut-off values .eg. -------------------------------------------------------------------------------- data(mayo) str(mayo) attach(mayo)

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

Hola, Marta, Por lo que he podido ver tus datos ya tienen calculados las tasas de verdaderos y falsos positivos (TPR y FPR). También parece que los tienes ordenados por la variable FishSpeed y supongo que también por las que parecen marcas de tiempo. No necesitas ROCR porque con un simple plot te sale algo parecido a una curva. Eso sí, veo que son medidas repetidas en el tiempo para cada valor de

Dear R Helpers, A few weeks ago I asked for some help on how to accomplish modifications to data in a set of data frames. As part of that request I mentioned that I realized that one way to accomplish my goal was to put the data frames together in a list but that I was looking for a way to do it with data frames and a loop because I "believe the better thing is to work df by df for my

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:

Dear all, I am using the "caret" Package for predictors selection with a randomForest model. The following is the train function: rfFit<- train(x=trainRatios, y=trainClass, method="rf", importance = TRUE, do.trace = 100, keep.inbag = TRUE, tuneGrid = grid, trControl=bootControl, scale = TRUE, metric = "ROC") I wanted to use ROC as the metric for variable

Dear User R It's been a pleasure talking with you. I am newcomer use R. Would you please help me how to translate the script below to "R" script? * Area under receiver operating characteristic (AU-ROC) predict r1m1p, p roctab malaria r1m1p, graph summary * Area under receiver operating characteristic (AU-ROC) curve predict r1m2p, mu roctab malaria r1m2p, graph summary