similar to: Generating R plots through Perl

Hi this is my first post. I am trying to run a simulation for a computer playing Von Neumann poker and adjusting it's expectation of an opponent's behavior according to how the opponent plays. This program involves random generation of "hands" and shifting of parameters. However, when I run the code, no errors come up, but the program doesn't do anything. Could someone

Thanks for the tip using a smoothing technique before plotiing in order to get a curve instead of a line connecting the observations. But that's not the solution for my main problem with the "unclean" line plot. In order to show my problem let's take this simple example: > xval <- c(1, 2, 3, 4, 5, 6, 7, 8) > yval <- c(10, 30, 40, 50, 70, 90, 100, 110) > plot

Hi, I am applying the following code to map pca loadings onto a 3d grid, my problem is this - the output only plots the spheres in the requested color (in this case "red") for the first argument. The sphere from the second argument appear as flat dark circles. Also the text3d() command only seems to work for a couple of the positions, with no text added in most cases. Could anyone offer

Hi all, I have this problem with lattice that xyplot() won't draw some of my axis labels if the type (i.e. the relation argument) of scales is set as free. For example, in the plot below, I would want it to also show: 1. the labels E1,...E6 below the 10th panel (i.e. 3rd row, 2 col)....just as it is now done below the 12th panel.... 2. as well as the labels (2,4,6,8) on the top of panels 1

Hello again I have modeled a tree using rpart, with the DV being a log transformation of the variable I am really interested in (I transformed the DV due to extreme skewness). By default, text.rpart labels the nodes with the value of yval, which in this case is not what I want; I'd like the labels to be on the original metric, but label in text.rpart requires a "column name of

Dear R users: I have a dataset with two variables (>20000 observations, two samples from same subject) and I used "kernSur" from library(Genkern) to get a estimated bivariate density and corresponding plots as follows: new.data.normal<-data.normal[!is.na(data.normal[,2]),] x<-new.data.normal[,2] y<-new.data.normal[,3] op <- KernSur(x,y, xgridsize=50, ygridsize=50,

Hi. How do I plot the straight line and r? in a scatter plot using a simple file x~y? Sueli Rodrigues Eng. Agr?noma - UNESP Mestranda - USP/ESALQ PPG-Solos e Nutri??o de Plantas Fones (19)93442981 (19)33719762

Hi, I am trying to use the rpart library with my own set of functions on a survival object. I get an immeadiate segmentation fault when i try calling rpart with my list of functions. I get the same problem with the logrank example from Therneau,s S-rpart library though their anova example works. Should I report this as a bug, as even if my functions are structured improperly, that should lead to

Dear R community, I've been writing simple functions for the past year and half and have come across a similar problem several times. The execution of a function within my own function produces NaN's or fails to execute as intended. My conundrum is that I can execute the function outside of my function without error, so it's difficult for me, as a novice functioneer, to figure out

Depending on the setting of par()$usr, the 'at' setting in mtext(.., adj=0, outer=T) may cause the text to appear in an anomalous position (e. g. in the first instance below, at the left of the plot region rather than at 'at=0' in the figure region), or the text may not appear at all. If one does not set the 'at' parameter the text appears (with 'adj=0') on the

Dear R users, I'm working with the rpart package and want to evaluate the performance of user defined split functions. I have some problems in understanding the meaning of the xval argument in the two functions rpart.control and xpred.rpart. In the former it is defined as the number of cross-validations while in the latter it is defined as the number of cross-validation groups. If I am

Dear R's I'm trying to use specific rather than random cross-validation groups in mvpart. The man page says: xval Number of cross-validations or vector defining cross-validation groups. And I found this reply to the list by Terry Therneau from 2006 The rpart function allows one to give the cross-validation groups explicitly. So if the number of observations was 10, you could use

Hi all, Looking for tips on how I might more optimally solve this. I have time series data (samples from a force sensor) that are not guaranteed to be sampled at the same time values across trials. ex. trial time x 1 1 1 1 5 4 1 7 9 1 12 20 2 1 0 2 3 5 2 9 10 2 13 14 2 19 22 2 24 32 Within each trial I'd like to use linear interpolation between each successive time sample to fill in

Hello All, Am I misreading the documentation? The text.rpart documentation says: "label a column name of x$frame; values of this will label the nodes. For the "class" method, label="yval" results in the factor levels being used, "yprob" results in the probability of the winning factor level being used, and ?specific yval level? results in the probability of

I tried using rpart, as below, and got this error message "rpart Error in yval[, 1] : incorrect number of dimensions". Thinking it might somehow be related to the large number of missing values, I tried using complete data, but with the same result. Does anyone know what may be going on, and how to fix it? I have traced two similar error messages in the Archive, but following the

All, I'm trying again with a slightly more generic version of my first question. I can extract the plotted values from hist(), boxplot(), and even plot.randomForest(). Observe: # get some data dat <- rnorm(100) # grab histogram data hdat <- hist(dat) hdat #provides details of the hist output #grab boxplot data bdat <- boxplot(dat) bdat #provides details of the boxplot

I am having trouble getting smooth-appearing curves in figures produced as windows metafiles using R (R-1.1.1 on Windows 98). When I import them into a word processor (either MS Word 97, or WordPerfect 9.0), the figures appear only slightly bumpy on screen, but when printed, there is a clear jaggedness reminiscent of aliasing. Is there a fix for this (if the answer is "upgrade to 1.2",

Can somebody please take a look at this and tell me whats going wrong? It seems to be parsing wronly around the 'if' statement and gives me a directory listing. Thanks in advance Tom N.B. datan is an invented dataset xvals<-c(1,0.4,0.2) datan<-data.frame(s1=c(3,4,5),s2=c(5,5,5),s3=c(21,55,34),s4=c(5,3,2)) datan$sint<-NA datan$sgrad<-NA for(icount in 1:dim(datan)[1]) {

Hi R-users, I have a collection of dataframes and know how to build a string that refers to it, in this example, name_infra_alg_inc. Then, I have a character string yval, which the user can select from a drop down list. It contains the column names of the dataframes. assign(paste(name_infra_alg_inc, "ci", sep="."), ci(get(name_infra_alg_inc)[[yval]], confidence=0.95)) My

I use ROCR to plot multiple runs' performance. Using the sample code as example: # plot ROC curves for several cross-validation runs (dotted # in grey), overlaid by the vertical average curve and boxplots # showing the vertical spread around the average. data(ROCR.xval) pred <- prediction(ROCR.xval$predictions, ROCR.xval$labels) perf <- performance(pred,"tpr","fpr")