search for: xval

...larification: After each round, an uneven coin (90/10 probability) is flipped to see if the game continues (hence the while loop). And every 10 hands, the noncomputer player changes strategy (hence the if...modulus 20 statement) Thanks lambda=0.8 game=1 count=0 a=0.1 b=0.7 x=numeric() y=numeric() xval=x yval=y while(game==1) { count=count+1 x[count]=runif(1,0,1) y[count]=runif(1,0,1) if ((count%%20)<10) { if (x[count] > 0.15 & x[count]< 0.65) { if(x[count]>y[count])...

...e example below) or 'error.bars', to draw only upper error bar (upper CI) if the bar value (mean) is positive and the lower error bar (lower CI) if bar value is negative? CI.plot <- function(mean, se,length, ylim=c(-5, max(CI.H)), ...) { CI.H <- mean+se CI.L <- mean-se xvals <- barplot(mean, ylim=ylim, ...) # Plot bars arrows(xvals, mean, xvals, CI.H, angle=90,length=length) arrows(xvals, mean, xvals, CI.L, angle=90,length=length) } CI.plot(D,SE,0.01) thanks, -- \m/ [[alternative HTML version deleted]]

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 > rpart( y ~ x1 + x2,...

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 correct this means that for xpred.rpart, xval denots the number V of one V-fold cross v...

...I need (see code below), but 2 things I can't get: 1. How to get "Jan","Feb","Mar" on the x=axis instead of 1:3? 2. How to get "T"s on the end of my error bars like you have in standard scientific plots? Any comments gratefully received! Thanks, Toby xvals=1:3 #couldn't get it to be "Jan, Feb, Mar" on the x-axis rgrT1=c(10,20,30) errbarsT1lo=c(0.5830952,0.3741657,0.8944272) errbarsT1up=errbarsT1lo rgrT2=c(25,30,35) errbarsT2lo=c(1.356466,3.535534,1.140175) errbarsT2up=errbarsT2lo minx=min(xvals);maxx=max(xvals) miny=min(rgrT1-errbarsT1...

...r this in my code to avoid it. I appreciate the help. Thanks. Below is the reproducible code: mixnbinom=function(y,k1,mu1,k2,mu2,prob,eps= 1/100000){ new.parms=c(k1,mu1,k2,mu2,prob) err=1 iter=1 maxiter=100 hist(y,probability=T,nclass=30,col="lightgrey",main="The EM algorithm") xvals=seq(min(y),max(y),1) lines(xvals,prob*dnbinom(xvals,size=k1,mu=mu1)+ (1-prob)*dnbinom(xvals,size=k2,mu=mu2),col="green") while(err>eps){ if(iter<=maxiter){ lines(xvals,prob*dnbinom(xvals,size=k1,mu=mu1)+ (1-prob)*dnbinom(xvals,size=k2,mu=mu2),lty=3) } bayes=(prob*dnbinom(y,size=k1,...

...sion from: (NULL) (139.133.7.38) I think you should have better examples on the ?plot man page, if you don't mind me saying. Can I suggest something like this, which would probably stop so many emails to the R help about how to put on error bars Cheers, Toby M ****************************** xvalsT1=1:3 yvalsT1=c(10,20,30) errplusT1=c(2,3,4) errminusT1=c(9,8,7) xvalsT2=1:3 yvalsT2=c(30,35,40) errplusT2=c(12,13,14) errminusT2=c(1,2,3) treatment=c(rep("T1",times=length(xvalsT1)),rep("T2",times=length(xvalsT2))) xvals=c(xvalsT1,xvalsT2) yvals=c(yvalsT1,yvalsT2) errplus=c(e...

...t <- c(0.00000, 26.24551, 61.78180, 86.88254, 221.75480) m <- c(48.591707, 15.655895, 12.284635, 5.758547, 0.000000) dat <- data.frame(t = t, m = m) m0 <- m[1] t0 <- t[5] nlls <- nls(m ~ (m0^(1/lambda) - (t * m0/t0)^(1/lambda))^lambda, start = list(lambda = 1), data = dat) xVal <- seq(0, t0, length = 10) mod.SE <- list() for(i in 1:length(xVal)){ z <- xVal[i] mod.SE[[i]] <- deltaMethod(nlls, "(m0^(1/lambda) - (z * m0/t0)^(1/lambda))^lambda")$SE } mod.SE This code executes deltaMethod() flawlessly (NOTE: [[1]] and [[10]] are supposed to be NaN'...

...If one does not set the 'at' parameter the text appears (with 'adj=0') on the far left of the plot region. I assume this is also anomalous; at all events it is the behaviour that I wished to circumvent. The function plot.test() demonstrates the behaviour: plot.test <- function(xval=0:4, pos=NULL){ oldpar<-par(oma=c(2,0,0,0)) on.exit(par(oldpar)) plot(xval,xval) if(is.null(pos))pos<-min(xval) print(pos) print(par()$usr) mtext(side=1,line=3.5,"Marginal text",adj=0,at=pos) mtext(side=1,line=0.5,"Outer text",outer=T, adj=0,at=min(xval)) } > plot.test...

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 (xval, yval, type="l") If you look to the result in the graphic window you will see that the line seems to exist of many points between the observations; e. g. between xval=1 and xval=2 the line...

...ot(dat) bdat #provides details of the boxplot output # the same works for randomForest library(randomForest) data(mtcars) RFdat <- plot(randomForest(mpg ~ ., mtcars, keep.forest=FALSE, ntree=100), log="y") RFdat ##But, I can't use this method in ROCR library(ROCR) data(ROCR.xval) RCdat <- plot(perf, avg="threshold") RCdat ## output: NULL Does anyone have any tricks for piping or extracting these data? Or, perhaps for steering me in another direction? Thanks, Tim From: "Tim Howard" <tghoward at gw.dec.state.ny.us> Subject: [R] ROCR.plot...

...for Windows are available, anyway)? Maybe metafiles have a coarse underlying resolution? The following code produces the problem (along with a postscript plot just to show that a smooth representation is possible): # PlotTest.R # 12/15/2000 # # Demonstrate some curiosities with windows metafiles xvals <- seq(0,1,length=101) yvals <- xvals^3 win.metafile(file="test.wmf",width=4,height=3.5, pointsize=12) plot(xvals,yvals,type="l") dev.off() postscript(file="test.eps",horizontal=FALSE,width=4,height=3.5, pointsize=12) plot(xvals,yvals,type=&...

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") plot(perf,col="grey82",lty=3) plot(perf,lwd=3,avg="vertical",spread.estimate="boxplot",add=TRUE) I can follow the code and plot without any pro...

...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, correlation=0.4968023, xbandwidth=1, ybandwidth=1) #3D density plot persp(op$xvals, op$yvals, op$zden, theta=30,phi=10,expand=0.5,ltheta=120, xlab="TECH3661.A",ylab="TECH3661.B",zlab="Prob",col="pink", , main="3D DENSITY PLOT-TECH3661 ", sub=" TECH3661.A AND TECH3661.B", box = T, axes = TRU...

...something that would retain the > > adaptability of integrate(). > > Yesterday, I've suggested to use approxfun(). Did you consider my > suggestion? Below is an example. > > N <- 500 > x <- rexp(N) > y <- rank(x)/(N+1) > empCDF <- approxfun(x,y) > xvals <- seq(0,4,.01) > plot(xvals,empCDF(xvals),type="l", > xlab="Quantile",ylab="Cumulative Distribution Function") > lines(xvals,pexp(xvals),lty=2) > legend(2,.4,c("Empirical CDF","Exact CDF"),lty=1:2) > > > It's possible t...

...ce a pdf file with no data (i.e. the plot data is not getting passed to the file). It seems that the pipe connection created via Statistics::R cannot produce a graphics device window to save. A very simple version of the commands that I am using in my Perl program are as follows: $R->send(qq (xVal <- c(1,2,3,4,5,6))); $R->send(qq (yVal <- c(3,5,2,6,1,5))); $R->send(qq (pdf("C:/Test Environment/R/perlPlotTest.pdf"))); $R->send(qq (plot(xVal, yVal))); $R->send(qq (graphics.off())); As the code indicates, I am using R's pdf function to create a pdf file contai...

hi I'm learning R and making some examples. One of them is that for given distribution I show density function, distribution function expected value and variance(?). I know EX <- function(xval,xprob) sum( (xval*xprob) ); where xval is vector of values and xprob vector of probabalities, but DX <- function(xval,xprob) EX((xval^2),xprob) - (EX(xval,xprob))^2; doesn't work as I thought. I've looked intto FAQs and archives but my question is probably too simple. Can somebody tell...

Hello again I'm trying to put error bars onto a barplot. I've tried something that Bill Simpson suggested a while ago, ie: x<-c(1,2,3,4,5) y<-c(1.1, 2.3, 3.0, 3.9, 5.1) ucl<-c(1.3, 2.4, 3.5, 4.1, 5.3) lcl<-c(.9, 1.8, 2.7, 3.8, 5.0) plot(x,y, ylim=range(c(lcl,ucl))) arrows(x,ucl,x,lcl,length=.05,angle=90,code=3) #or segments(x,ucl,x,lcl) but I can't get it to work on a

...;) >barplot2(meanapAprilactivity, names.arg=speciesnames, col=columncolor, xlab="Species", ylab="Soil acid phosphatase activity (nmol/h/g)", ylim=c(0,1000), plot.ci=T, ci.l=apAprilminusordered, ci.u=apAprilplusordered, cex.lab=1.5)#FinalGraphs>aPApril_Genus.pdf >xvals<-barplot2(meanapAprilactivity, col=columncolor, xlab="Species", ylab="Soil acid phosphatase activity (nmol/h/g)", ylim=c(0,1000), plot.ci=T, ci.l=apAprilminusordered, ci.u=apAprilplusordered, cex.lab=1.5)#FinalGraphs>aPApril_Genus.pdf >text(xvals,par("usr&q...

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]) { yvals<-c(datan[icount,4],datan[icount,3],datan[icount,2]) if((is.na(yvals[1]) + is.na(yvals[2]) + is.na(yvals[3]))<2) { g<-l...