similar to: how to create normal qqplot with the 95% confidence interval

Hi, We could use qqplot to see how two distributions are different from each other. To show better how they are different (departs from the straight line), how is it possible to plot the straight line that goes through them? I am looking for some thing like qqline for qqnorm. I thought of abline but how to determine the slope and intercept? Best wishes, Carol

I am a beginner in R, so please don't step on me if this is too simple. I have two data sets datax and datay for which I created a qqplot qqplot(datax,datay) but now I want a line that indicates the perfect match so that I can see how much the plot diverts from the ideal. This ideal however is not normal, so I think qqnorm and qqline cannot be applied. Perhaps you can help? Ralf

Hi, I'm trying to create a qqplot with reference to a Weibull distribution including a reference line. This is my current code: lights.data <- scan("lights.dat") #Generate Weibull quantiles prob.grid <- ppoints(length(lights.data)) prob.quant <- qweibull(prob.grid , 1.5,4) #Draw QQ plot qqplot(prob.quant,lights.data) #add red reference line qqline(lights.data,col = 2)

Hi all, I am an R newbie, and I have a question about scripting. I have the following lines which I want to put int\ o a script which I can call from the shell of a Mac/Linux machine : myrns <- read.csv(file="/Users/vihan/test.csv",sep="",header=FALSE) qqnorm(myrns) qqline(myrns) This works fine on an interactive R session. However, as I understand the basic framework of

Dear People, In a qqplot I am doing, I get lines/points that are very thick. I've tried setting the lwd variable to 0.1, but it doesn't seem to have any effect. Also, I have set the value of lty to dashed, but I still get dots. The command looks like qqplot(cdf.inv(seq(0,1,length=size),theta,pos,len),empmargdistvec(len,theta,pos,size), xlim=c(-theta,theta), ylim=c(-theta,theta),

Hi Everyone, I want to make 3 lines on the same graph (not as subplots, all in the same window, one on top of each other) and I want them to be quantile-quantile plots (qqplot). Essentially, I am looking for the equivalent of Matlab's "hold on" command to use with qqplot. I know I can use 'points' or 'lines', but these do not give me a qqplot (only appear to work

Hello, I would like to use qqplot() to compare two experimental distributions. But I do not understand how qqplot() compute quantiles. In fact, quantile() do not return the same results. Thank you for your help. Vincent.

Hi All, I am trying to plot 4 graphs on to 1 page using layout(...), or par(mfcol = c(...)); with the function QQplot from the package PerformanceAnalytics. The problem is that, no matter what order I use, it only plots 3 graphs on to 1 page and the last QQplot is shunted to the next page. Also, this only happens to the QQplot, i.e. there is no problem with 4 Histograms. set.seed(1033) data

Full_Name: Matthias von Davier Version: 1.2.0 OS: linux Submission from: (NULL) (144.81.31.148) pairs(NxK_Matrix,panel=qqplot) produces a message Error in pairs.default(NxK_Matrix,panel=qqplot) : The panel function made a new plot best regards and a happy new year -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read

>>>>> On Tue, 31 Aug 1999 14:57, Werner Stahel <stahel@stat.math.ethz.ch> said: WSt> Here is a suggestion. It seems that qqplots, comparing a sample WSt> to a distribution other than the normal, are not explicitly WSt> available in S or R. I found (in S-plus / Trellis it is, see below) WSt> qqplot(y, rt(300, df = 5)) WSt> as an

Dear Community, I want to identify outliers in my data. I don't know how to use identify command in the plots obtained. I've gone through help files and use mahalanobis example for my purpose: NormalMultivarianteComparefunc <- function(x) { Sx <- cov(x) D2 <- mahalanobis(x, colMeans(x), Sx) plot(density(D2, bw=.5), main="Squared Mahalanobis distances, n=nrow(x),

Hi! <http://r.789695.n4.nabble.com/file/n4651293/qq.png> We are stuck with a problem considering the qqplot of a dataset. We are trying to discover what kind of distribution this is. We already tried to normal, exponential or the logaritmical distribution but none of those are able to solve our problem. Is there someone able to tell us what kind deformation we should try? (I'm

Folks, Normally, in a data frame, one observation counts as one observation of the distribution. Thus one can easily produce a CDF and (in Splus atleast) use cdf.compare to compare the CDF (BTW: what is the R equivalent of the SPlus cdf.compare() function, if any?) However, if each point should not count equally, how can I weight the points before comparing the distributions? I was thinking of

Hi Guys, I am having a real hard time trying to figure out for microarry. Here is my code One-Sample t-Test dim(data.sub) [1] 10000 140 ##there are 10000 probesets and 140 columns hist(data.sub) ## Histogram. Identify if the probesets are normal distributed q<-rnorm(10000) ##generate 10000 random, normal distributed values qqplot(data.sub,q)) ##Show the plot of the probeset

Hy, I have dowloaded the R-version for Windows. I would want to plot different pictures on the same device, but I am not able to do it (i.e I would like make 2 qqplot on the same graphic). Can you help me? Thanks in advance Davide reply to: d.tarfanelli at libero.it -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I have a data vector x. When I try qqline(x) I get the following error: Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet And a blank plot appears. Can anybody help? What am I doing wrong? Thanks, Scotty _________________________________________________________________ Contest [[alternative HTML version deleted]]

I have written a function to emulate minitab's QQ plotting output (with SW test and AD test results on the graph): mtab.norm<-function(x) { library(nortest) library(lattice) x<-as.numeric(x) x<-as.vector(x) plot.ht<-4.6 plot.wd<-4.6 pt.ht=plot.ht/5 txt.sz<-(plot.ht/7.5) X11(width=plot.wd, height=plot.ht, bg='gray96') qqplot(x, pch=16, cex=pt.ht,

Hi, R friends. I had some difficulty with the following code: qqnorm(freq, log='y') qqline(freq) as the line drawn was seemingly random. The exact data I used appears below. After wandering a bit within the source code for "abline", I figured out I should rather write: qqnorm(freq, log='y') par(ylog=FALSE) qqline(log10(freq)) par(ylog=TRUE)

Hi all, I am trying to test wheater the distribution of my samples is normal with QQ plot. I have a values of water content in clays in around few hundred samples. Is the code : qqnorm(w) #w being water content qqline(w) sufficient? How do I know when I get the plots which distribution is normal and which is not? Thanks, m [[alternative HTML version

How do I generate a value in R from a poisson distribution with mean 20? Thanks! -- View this message in context: http://www.nabble.com/Generating-a-value-tf4922234.html#a14086120 Sent from the R help mailing list archive at Nabble.com.