similar to: Suggestion for qqplot() improvement

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)

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)

>>>>> "WSt" == Werner Stahel <stahel@stat.math.ethz.ch> writes: [to me privately] WSt> I do not want to call this a bug, but it bugged me. Please try the WSt> following: WSt> tform <- sqrt(RADAI) ~ sqrt(RADAI.e) + TAGE.ej + SPITAL + ARZT + DAS28 + WSt> SJC + TJC + DGA + HAQ + PGA + PAIN + YEAR.SYM + YEAR.DIA + WSt> ALTER +

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 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))

Hello, Our professor asked us to do probability plotting using weibull paper, exponential paper, normal, log-normal paper, etc. I know I can create Q-Q plot for normal dist. and see if all te points are on one line. How do I go about other distributions? I tried generating different samples and use the general qq function. However, I could not do it since I don't know the population

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, 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)

In the following special case, seq fails to give the right answer (which is 0 ) > seq(0,0,1) Error in if (dd < sqrt(.Machine$double.eps)) return(from) : missing value where logical needed For any other equal from and to , it works: > seq(1,1,1) [1] 1 The error occurs in the statement dd <- abs(del)/max(abs(to), abs(from)) of seq.default -- for obvious reasons.

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

splom() doesn't complain here, but writes no names in the diagonal boxes. What am I missing? I believe that I need to add something like grid.text(x, ...) to the diagonal panel, but I don't know how to get it cycle through the column labels. And should varname.col = 'blue', varname.cex = 1 be inside the diag.panel() function? splom(szw[, n], pscales = 0, diag.panel

David, Duncan, > Hi > > Following on David's rate argument > > try (with modifications of pch and grid) > > rate <- 1/4 > shape = 8 > rate = c(rep(1/4,100),rep(1/3,100)) I don't think the problem is related to the rate argument, which can well be vectorized, as is the case for a number of arguments in distrib functions in R (note that you are redefining it

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

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

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

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 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.

In qqmath, how would one go about having 'distribution' change with panel.number? I've tried set.seed(1) mydata <- data.frame(ind = factor(rep(2:4, each = 100))) mydata$val <- rt(300, df=rep(2:4, each = 100)) plot<-qqmath(~ val | ind, layout=c(3,1), data = mydata, prepanel = function(x, distribution, ...) {