similar to: A plotting question - how to get error bars?

Full_Name: TOBY MARTHEWS Version: 2.1.1 OS: Windows XP Submission 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)

Hi, The code below is giving me this error message: Error in while (err > eps) { : missing value where TRUE/FALSE needed In addition: Warning messages: 1: In dnbinom(x, size, prob, log) : NaNs produced 2: In dnbinom(x, size, prob, log) : NaNs produced I know from the help files that for dnbinom "Invalid size or prob will result in return value NaN, with a warning", but I am not able

How can I condition any error bar function that use the arrows() function, such as 'CI.plot' (see 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

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",

Here's one way. Suppose your "time series" is in a vector called "x". top10 <- sort(x, decreasing=TRUE)[1:10] mean.index <- mean(which(x %in% top10)) HTH, Andy > -----Original Message----- > From: James Brown [mailto:jdb33 at hermes.cam.ac.uk] > Sent: Tuesday, September 23, 2003 7:51 AM > To: r-help at stat.math.ethz.ch > Subject: [R] Rank and

Hi, >I would like to rank a time-series of data, extract the top ten data items from this series, determine the >corresponding row numbers for each value in the sample, and take a mean of these *row numbers* (not the data). >I would like to do this in R, rather than pre-process the data on the UNIX command line if possible, as I need to >calculate other statistics for the series.

Dear list, I have multiple (BWidget) listboxes in the same toplevel window. The problem is, if I select (by left clicking) on one of those listbox elements, the current selection in the *other* listboxes is cleared! Anybody knows how I can prevent this? Here's my code (sorry not complete): (E.g. If I select an X value, I'd lose the Y value I selected before) gui.create.tab.general <-

Hi, The problem is that I would like to do an interaction plot with intervals based on Tukey's honestly significant difference (HSD) procedure, but I do not know how to do it in R. I have 3 factors "A", "B" and "C" and a response variable "response". I would like to study a model where there are main effects and second order interaction effects.

Hi! With the following script, I'm trying to make a demonstration of a Confidence Interval, but I'm observing some differences on tails. # Teste de média entre uma amostra e uma população normal # Autor: Raphael de Freitas Saldanha # Agosto de 2008 n <- 200 # Sample size xbar <- 100 # Sample mean s <- 2 # Sample SD nc <- 0.95 # Confidence level (95%

Hello, Using this data: http://n4.nabble.com/file/n1676330/US_Final_Values.txt US_Final_Values.txt and the following code i got the image at the end of this message: US.final.values<-read.table("c:/tmp/US_Final_Values.txt",header=T,sep=" ") US.nls.1<-nls(US.final.values$ECe~a*US.final.values$WTD^b+c,data=US.final.values,start=list(a=2.75,b=-0.95,c=0.731),trace=TRUE)

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]) {

While building a package, I see the following: * checking R code for possible problems ... NOTE cheat.fit: no visible binding for global variable 'Zobs' plot.jml: no visible binding for global variable 'Var1' I see the issue has come up before, but I'm having a hard time discerning how solutions applied elsewhere would apply here. The entire code for both functions is below,

Hi all I'm trying to create a three-dimensional wireframe-type plot, much like the screenshot shown at http://www.r-project.org/screenshots/volcano-persp.jpg In my case, I'm trying to show a density estimate of two-variable system, using the GenKern package. I've used the image() and contour() to create a nice shaded plot, but I've found a 3d plot is often easier for the

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,

Dear list, My query follows on from a question I posted a few days ago. I have the following 2 sets of data: wetMeans[1] 9.904762[2] 6.344828[3] 6.346154[4] 6.855769[5] 9.074324[6] 9.953988[7] 13.482966[8] 14.546053[9] 10.841584[10] 9.752033[11] 6.739336[12] 8.955056burnMeans[1] 0.06214286[2] 0.05396552[3] 0.04096154[4] 0.05302885[5] 0.05831081[6] 0.07392638[7] 0.29969940[8] 0.25596217[9]

Hej, Calling newuoa (from the minqa package) makes R crash when the package rgl is loaded first. This however only on certain selected data. The data used for testing (saved to 'bugs.R'): xvals = c(1,2,4,5,7,8,9,10,11,12,14,15,16,18,19,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36) yvals =

Hello all, Hoping that there is a fairly simple solution to my query... I'm trying to overlay a line plot of some data onto a barplot of different data. The y-axes are different for each set of data but the x-axes are the same (1:12, corresponding with 12 months of observations). The problem I'm having is that the centre of the bars and the points on line don't match up, which is

I am making a barplot using barplot2 from gplots where each bar represents a specific tree species. I have formatted the species names on the x-axis so that the genus name is above the species name and have then rotated the labels 45 degrees to save room. This is my code: >columncolor<-c("grey20", "grey20", "grey20", "grey70",

I am trying to tweak how my categorical x-axis labels are formatted in my bar graph. Specifically, I would like to a) decrease the spacing between lines (e.g. spacing between Dialium and guianensis) b) right justify the text and c) have each species name align with the center of the corresponding bar graph. A simplified version of my code thus far is as follows. I am using RStudio v.

Not sure about the correctness for this list, but anyway... I notices some indesireable behaviour in interaction.plot. The scaling of the x-axis labels discards the overall settings for the ''cex'' attribute, leading to unscaled labels. The source for this behaviour is the line mtext(xlabs, 1, at = xvals) in interaction.plot. to get this function to perform conform the manual,