similar to: Fitting a line to a qqplot's points?

Suppose you have a vector of data in x and response values in y. How do you plot together both the points (x,y) and the curve that results from the fitted model, if the model is not y ~ x, but a higher order polynomial, e.g. y~poly(x,2)? (In other words, abline doesn't work for this case.) Thanks, --Paul -- Paul Lynch Aquilent, Inc. National Library of Medicine (Contractor)

Is there a download page for mongrel_cluster? I see that "gem install mongrel_cluster" works, but I can''t see where it''s coming from. Usually gems have some sort of project page somewhere. -- Paul Lynch Aquilent, Inc. National Library of Medicine (Contractor)

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,

Hi, I'm trying to do a linear regression style one-way ANOVA using some data in a data frame, and (perhaps because I am still relatively unfamiliar with both R and statistics) what I thought I should do was to make the data frame into a factor. By that I mean that I have a data frame whose column labels are the levels of the factor, and the values in the frame are numeric values for the

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

This morning I tried to see if I could find the r-help mailing list on Google Groups, which has an interface that I like. I found three Google Groups ("The R Project for Statistical Computing", "rproject", and "rhelp") but none of them are connected to the r-help list. Is there perhaps some reason why it wouldn't be a good thing for there to be a connected

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

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

Suppose you have 4 related vectors: a.id<-c(1:25, 1:25, 1:25) a.vals <- c(101:175) # same length as a.id (the values for those IDs) a.id.levels <- c(1:25) a.id.ratings <- rep(letters[1:5], times=5) # same length as a.id.levels What I would like to do is specify a rating from a.ratings (e.g. "e"), get the vector of corresponding IDs from a.id.levels (via

Hi, I've downloaded R-2.6.2-win32.exe (base) from two CRAN sites (http://mirrors.ibiblio.org/pub/mirrors/CRAN/ and http://lib.stat.cmu.edu/R/CRAN/) and for both of those sites the expected MD5 hash is reported to be: ed512872818707f27ca05f08be7363c2 *R-2.6.2-win32.exe (See, for example, http://lib.stat.cmu.edu/R/CRAN/bin/windows/base/md5sum.txt). However, when I compute the MD5

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,

>>>>> 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 am attempting to use the R Commander Graphs Quantile-Comparison functionality on a dataset, to compare with a triangular distribution. I have the package triangle. My question is on the syntax of how to specify the parameters of the theoretical distribution in the Parameters field of the dialog box. For example, the theoretical distribution has min of 3000, max of 5000, mode of 4000. When

Dear Lu Wei, > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Lu Wei > Sent: Sunday, July 23, 2017 12:27 AM > To: r-help at stat.math.ethz.ch > Subject: Re: [R] cannot use package RcmdrPlugin.plotByGroup > > On 2017-7-23 6:21, Fox, John wrote: > > Dear Lu Wei, > > > > I'm the author of the Rcmdr package

Dear R community. I am using the identify() function to identify outliers in my dataset. This is the code I am using: #################################################################### # Function to allow identifying points in the QQ plot (by mouseclicking) qqInteractive <- function(..., IDENTIFY = TRUE) { qqplot(...) -> X abline(a=0,b=1) if(IDENTIFY) return(identify(X))

On 2017-7-23 20:41, Fox, John wrote:> ... > The Rcmdr uses the qqPlot() function in the car package. In the next > version of the car package, qqPlot() will be able to plot by groups, > and when that happens, I'll incorporate the feature in the Rcmdr. > > More generally, however, if you learn to write R commands you'll be > able to make customized plots. It would be

Dear All, this is my first post to the R-help, so please don't be too strict. My problem concerns a QQ-Plot: I want to show how well empirical samples match with a theoretical distribution. The theoretical distribution has got several parameters, but I made it to fit via ML. Anyway, the theoretical function gives me the density for a given data point x. As far as I'm

I'm looking for goodness of fit tests for gamma distributions with large data sizes. I have a matrix with around 10,000 data values in it and i have fitted a gamma distribution over a histogram of the data. The problem is testing how well that distribution fits. Chi-squared seems to be used more for discrete distributions and kolmogorov-smirnov seems that large sample sizes make it had to

Hi, For some dataset I have made a histogram, boxplot en qqplot. http://r.789695.n4.nabble.com/file/n4634093/Naamloos.jpg Investigate the data with the given functions for making QQ-plots and find an appropriate location-scale family for the underlying distribution of this sample. Apart from giving a proper location-scale family, also specify the member of the location-scale family that is

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