similar to: QQplots of probability vector data

>>>>> 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

I think qqline does not do exactly what it is advertised to do ("`qqline' adds a line to a normal quantile-quantile plot which passes through the first and third quartiles."). Consider the graph: tmp <- qnorm(ppoints(10)) qqnorm(tmp) qqline(tmp) The line (which I expected go through all the points), has a slightly shallower slope than does the points plotted by qqnorm. I think

Dear list-reader, by running the following script: library(zoo) sessionInfo() search() packageDescription("zoo") data(EuStockMarkets) dax <- as.zoo(EuStockMarkets[1:10, "DAX"]) daxr <- diff(log(dax)) identical(as.vector(qnorm(daxr)), qnorm(coredata(daxr))) qqnorm(coredata(daxr)) qqnorm(daxr) qqnorm() produces an error: > qqnorm(daxr) Fehler in if (xi == xj) 0L

Dear R help, I tried to plot two qq plots in the same window using the code below.? Somehow it is plotting only one at a time.?? I borrowed the print function from xyplot. ? pdf("QQplotCorrUncorr.pdf") qq1<-qqPlot(residuals(fm), main="QQ plot for Correlated Model") qq2 <-qqPlot(residuals(fma), main="QQ plot for Uncorrelated Model") print(qq1, pos = c(0.0,

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

Stock returns and other financial data have often found to be heavy-tailed. Even Cauchy distributions (without even a first absolute moment) have been entertained as models. Your qq function subtracts numbers on the scale of a normal (0,1) distribution from the input data. When the input data are scaled so that they are insignificant compared to 1, say, then you get essentially the

My routine (below) works OK but misbehaves if the on-screen plot is made wider using the mouse. The problem is caused by using par("usr")[1] - 0.07 * (par("usr")[2] - par("usr")[1]) to locate two items on the y-axis. The rest of the labeling is controlled by the "line=0" parameter setting. Of course resizing changes the absolute plot width, and

dear all, it will just take you a minute to tell me the difference between qnorm and qqnorm. are they same or is there any difference between them?? regards

Hello I am writing an article demonstrating how quantile plots work. In one figure, I generate 3 sets of normal data, and add different sorts of outliers to each. I then make 9 qqnorm plots, in a 3x3 array: Outlier1 Outler2 Outlier3 Dataset1 Dataset2 Dataset3 which I did using mfrow = c(3,3). I'd like to use the space on the page as efficiently as possible,so I

Hi- I wanted percentage labels on a qqnorm x axis. I used the following: #make up some data jt<-rnorm(100) #qqnorm with percentile x labels qqnorm(jt,axes=F,xlab="Percentiles") box() l<-c(1,5,10,30,50,70,90,95,99) axis(1,at=qnorm(l/100),label=l) which was ok for this data set. Does anyone have a more general solution which would allow one to specify the number of x labels

Do you know of a reference that discusses alternative choices for plotting positions for a normal probability plot? The documentation for qqnorm says it calls ppoints, which returns qnorm((1:m-a)/(m+1-2*a)) with "a" = ifelse(n<=10, 3/8, 1/2)? The help pages for qqnorm and ppoints just refer to Becker, Chambers and Wilks (1988) The New S Language (Wadsworth & Brooks/Cole),

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

I want to produce some boxplots (and qqnorm plots) for each of a series of groups. It is easy to produce the boxplots or qqplots by groups using either by() or tapply(), but the moment that I want unique labels for each boxplot, I seem to be stuck using a for loop to achieve the effect. For example: tapply(fstat$femur, fstat$race, boxplot) by(fstat$femur, fstat$race, boxplot) gives nicely

Here is my code, which plots three lines with errorbar. How could I add an extra line without errorbar to the plot? Thank you very much. beta.data <- data.frame ( method = rep(c("Wrong", "Correct", "Full Bayes"), each = T_obs), mean.beta = c(mean.beta1, mean.beta2, mean.beta3), t = rep(points, 3), std.beta = c(std.beta1, std.beta2, std.beta3) ) limits =

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 have been crashing R while using lattice. My system consists of a Mac Intel, R 2.5.1, lattice 0.15-5, and I plot through the default quartz. R crashes after plotting several lattice functions. Has anyone else encountered this problem and does anyone know the cause, or a solution? Is this a lattice:mac, lattice:quartz, Lattice:me issue? example... This crashes my system after plotting.

Hello all, (First of all, I'd like to thank all who replied to my previous question. I have never encountered such a helpful community before. Thanks for making a R so welcoming.) To calculate a quantile for normal distributions, one simply uses qnorm(1-a). But if I would want to do the same for a t-test function, how would I go about doing that? Is there a simple way to do it? (Yes, I

Hi, I'd like to partition a 2d probability density function into regions of equal probability. It is straightforward in the 1d case, like qnorm(seq(0,1,length=5)) but for 2d I'd need more constraints. Any suggestions for how to approach this? Is seems like a spatial sampling problem but I'm not sure where to look. Thanks for your time, Dave -- Dr. David Forrest drf at

I know this topic has had plenty of discussion in the last couple of days, but.... I've been trying to compare the effects of different fitted methods for systems of equations (OLS, SUR, 2SLS, 3SLS ) and would like to compare the residual plots (easy) and the qqnorm/qqplot of the fits for the different fitted methdos. For example, qqnorm( residuals( lm( q ~ p + f + a ) ) ) par( new = TRUE )

Hi, there. Is there any function in R to plot the probability-probability plot (PP plot)? Suppose I am testing some data against normal. Thanks. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O) 734-764-8263(fax) $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$