similar to: making multiple lines using qqplot

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

>>>>> 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

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.

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

hi everyone! season's greetings! is there any way that i can create a normal qqplot showing, aside from the qqline, the 95% confidence limits? thank you very much.. happy holidays! -- View this message in context: http://n4.nabble.com/how-to-create-normal-qqplot-with-the-95-confidence-interval-tp977727p977727.html Sent from the R help mailing list archive at Nabble.com.

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! <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

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),

Dear all, first I would like to tell you that I've been using R for two days... (so, you can predict my knowledge of the language!). Yet, I managed to implement some stuff related with the Long-Tail model [1]. I did some tests with the data in table 1 (from [1]), and plotted figure 2 (from [1]). (See R code and CSV file at the end of the email) Now, I'm stuck in the nonlinear regression

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

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

Dear all, I would like to ask you if R has a library that can work with different GPS formats For example  I have a string of this format N50° 47.513 E006° 03.985 and I would like to convert to GPS decimal format. that means for example converting the part N50° 47.513 to 50 + 47/60 + 513/3600. Is it possible to do that with R? What is the name of such a library? I would like to thank you in

I was surprised to find that just changing the base level of a factor variable changed the number of significant coefficients in the solution. I was surprised at this and want to know how I should choose the order of the factors, if the order affects the result. Here is the small example. It is taken from 'The R Book', Crawley p. 365. The data is at

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,

Dear list, I just tried to do the same thing, and did not find anything on a weighted qqplot. My weights are actually counts (positive integers). Here is a modification of qqplot, following Duncan Murdoch's suggestion. Any feedback would be welcome! Thanks, Jean-Christophe weighted.qqplot <- function (x, y, plot.it = TRUE, xlab = deparse(substitute(x)), ylab = deparse(substitute(y)),

I've made some normal plots of my data using qqplot, and now I would like to fit a line to the points on the plot and check the correlation coefficient to have a more objective measure of how straight the line is. Is there a simple way of doing that? (I'm still pretty new to R.) Thanks, --Paul -- Paul Lynch Aquilent, Inc. National Library of Medicine (Contractor)

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 Group, Here is some data. p <- runif(1000) # sample data groups <- rep(c(1,2),each=500) #conditioning variable mydata <- cbind(p,groups) n <- length(p) u <- (1:n)/(n + 1) # uniform distribution reference for qqplot logp <- -log(p,base=10) logu <- -log(u,base=10) qqplot(logp,logu) How can I make the above qqplot in lattice and/or ggplot2. The sample is uniform, and I take

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),

Given a set of integers of different values how do I calculate the minimum number of the largest of integers that are required, when summed, to equal 50% of the total sum of the the set? For example, > length(myTable$lgth) [1] 303403 > sum(myTable$lgth) [1] 4735396 I know through brute force that the N50 of the following set is 42 but I don't know how to solve this without iteration