similar to: Probability plotting with R

>>>>> 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 am trying with this question again: I would like to test few distributional assumptions for some behavioral response data. There are few theories about true distribution of those data, like: normal, lognormal, gamma, ex-Gaussian (exponential-Gaussian), Wald (inverse Gaussian) etc. The best way would be via qq-plot, to show to students differences. First two are trivial: qqnorm(dat$X)

Having solved this problem, I am posting this so that the next time I search for how to do this I will find an answer... Using qqmath(..., groups=num) creates a separate qq distribution for each group (within a panel). Using the 'col' or 'pch' argument does not (usually) work because panel.qqmath sorts the data (but not 'col' or 'pch') before plotting. Sorting

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

Hi Group, For the plot below, are there other ways I can use more of the plotting space. I've tweaked the parameters I know of. I could also put the plot titles inside the plot if there is a way to do that. Thanks for your input. Regards, Juliet p1 <- runif(1000) # sample data qp1 <- qqmath(~ -log(p1), data = as.data.frame(p1), distribution =

Dear R helpers, I generate a qq plot using the following function call. qqmath(~val|ind,data=xx ,distribution=function(p) qt(p,df=19) ,ylab="Sample Quatinles" ,xlab="Theoretical Quantiles" ,aspect=1 ,prepanel = prepanel.qqmathline ,panel=function(x,y) { panel.qqmathline(y, distribution=function(p) qt(p,df=19),col=2)

As a newbie to R, I'm still rather at a loss for finding information (the commands names can be rather arcane)so I'm just posting my question: I would like to estimate the shape coefficient of diverse distributions (Weibull, gamma and Tukey-Lambda specifically, but other could be of interest) - Does R have a PPCC utility to estimate such parameter?(maximum value of correlation coef)

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))

Hi, Is there a function that does percentile-percentile plot. I do not mean the qqplot. I need to plot the percentiles rather than points themselves. I am hoping for a plot that tells me that the x percentile of one data set corresponds to the y percentile of the other. for example a point on the plot of (.5, .2) will tell me that the 50th percentile of the first data and the 20th percentile of

Dear list, I've written a small utility function to add arbitrary legend(s) to a lattice graph (or a combination of them), much like the legend function of base graphics. I though perhaps it could be useful to someone else, or improved by suggestions. I understand this goes against the lattice paradigm somewhat, in that you short-cut the link between group variables and the

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, I want to create upper and lower 95% confidence intervals for a p-p plot of an empirical distribution with a theoretical gamma distribution. This is my code: x<-rgamma(100,shape=2, rate=1) # empirical data fitdistr(x,"gamma") # fit a gamma distribution dist<-pgamma(x,shape=1.9884256 ,rate=0.8765314 ) # fitted distribution, using the loglikelihood estimated parameters

Hi all, I'm trying to superimpose a rchisq density line over a histogram with something like: hist(alnlength) lines(density(rchisq(length(alnlength), 4)),col="red") But the rchisq line won't appear anywhere, Anyone knows what I am missing here? Thanks in advance, Albert.

Hi, Don't have a clue what teh following error message generated by this function call: qqmath( ~val|ind,data = xx ,distribution = function(p){ qt(p,df=20)} ,ylab="Sample Quatinles" ,xlab="Theoretical Quantiles" ,panel=function(x,y) { panel.qqmathline(y , distribution=function(p) qt(p,df=20)

Hello, I can't seem to make qqmath plot text. v <- rnorm(8) qqmath(~v) # this is ok, but qqmath(~v, panel=function(x, y) { points(x, y) text(0, 0, 'print me', cex=2)}) isn't ok. The axis frame is printed properly (ie, as in qqmath(~v)), but neither 'print me' nor the points show up on the graph. I can, however, see the upper half of the word 'me' in the

One of many scripts to produce 4 lattice plots on one page keeps throwing an error. I've tried manipulating the file to eliminate the error, but have not been able to do so. The error is: > source('bicarb.R') Error in source("bicarb.R") : bicarb.R:15:1: unexpected symbol 14: 15: hco33 ^ The 'h' is in column 0 so the caret would be column -1, but it's

Does the 'groups' option on qqmath just color the points differently in the main distribution or does it actually overlay separate quantile plots for each subset? I would like to be able to do the latter. --Rich Richard Kittler AMD TDG 408-749-4099

When I look at ppoints I see: ppoints<-function (x) { n <- length(x) if (n == 1) n <- x (1:n - 0.5)/n } However Venables & Ripley (2nd ed, p 165) say ppoints() should return (i-1/2)/n for n>=11; (i-3/8)/(n+1/4) for n<=10. The version below should work as described: ppoints<-function (x) { n <- length(x) if (n <= 10) (1:n - 0.375)/(n + 0.25) else (1:n - 0.5)/n

Hello ALL! Can anyone tell me how to specify qqmath() function with distribution qgamma? In help it is bit vague how to pass shape and scale parameters for gamma. Thank you in advance. Best, PM

First my excuses if I keep bugging everyone in this list, but I am a newbie, and tend to find some behaviour that looks unexpected to me; and I would really appreciate to be pointed to some location that allows me to understand more about this software. Here is my next question: > par(mfrow=c(1,1)) > qqnorm(rnorm(20)) > qqmath(rnorm(20)) > par(mfrow=c(3,4)) > for(i in