similar to: Difficulty with qqline in logarithmic context

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

Hi all, I'm modeling using lme in the nlme package. qqnorm makes plots just find, but when I try to add a line with qqline, I get the following error: "Error in sort.list(x, partial = unique(c(lo, hi))) : 'x' must be atomic for 'sort.list' Have you called 'sort' on a list?" For example > modelincr10<-lme(lruin~can.pos.num, data=rwushi30, random=(~1|

Hi, people. I met a little problem for which someone might have a solution. Let's say I have an executable file (named "pp.R") with this contents: #!/usr/bin/Rscript options(echo=TRUE) a <- 1 Sys.sleep(3) a <- 2 If I execute "./pp.R" at the shell prompt, the output shows the timely progress of the script as expected. If I use "./pp.R | tee

Hi, people. Executing the following command: hist(rpois(100,5), labels=TRUE) yields a graphic in which some labels are truncated (on an X11 device). The truncated labels are those over the highest bars. The hist function should ideally manage enough room for the labels, automatically. (Specifying ylim solves my problem, but yet, hist could be frienlier.) --please do not edit the

I have a data vector x. When I try qqline(x) I get the following error: Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet And a blank plot appears. Can anybody help? What am I doing wrong? Thanks, Scotty _________________________________________________________________ Contest [[alternative HTML version deleted]]

Hello R friends, I'm wondering why I get funny qqnorm() results. It seems that they should all be reflected in the normal qqline(). For instance: if I qqnorm() bimodal or uniform data I get a sigmoidal in which the qqnorm() points lie above the qqline() at -ve theoretical quantiles, and the qqnorm() points lie below the qqline() at +ve theoretical quantiles. Yet I expect such platykurtic

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

Here are another three problems with logarithmic scales: 1) segments() does not work with logarithmic scales. I suggest to change lines 962-973 in "plot.c": for (i = 0; i < n; i++) { if (FINITE(xt(x0[i%nx0])) && FINITE(yt(y0[i%ny0])) && FINITE(xt(x1[i%nx1])) && FINITE(yt(y1[i%ny1]))) { GP->col = INTEGER(col)[i % ncol];

Hi, people. The output produced by "?options" contains: 'expressions': sets a limit on the number of nested expressions that will be evaluated. Valid values are 25...500000 with default 1000. [...] and a bit further down: The 'factory-fresh' default settings of some of these options are [...] 'expressions'

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

Dear experts, I tried to learn about Box-Cox-transformation but found the following thing: When I had to add a constant to make all values of the original variable positive, I found that the lambda estimates (box.cox.powers-function) differed dramatically depending on the specific constant chosen. In addition, the correlation between the transformed variable and the original were not 1 (as I

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

Hi all, I am trying to test wheater the distribution of my samples is normal with QQ plot. I have a values of water content in clays in around few hundred samples. Is the code : qqnorm(w) #w being water content qqline(w) sufficient? How do I know when I get the plots which distribution is normal and which is not? Thanks, m [[alternative HTML version

Hi all, ########################################## dof=c(1,2,4,8,16,32) Q5=matrix(rt(100,dof),100,6,T,dimnames=list(NULL,dof)) par(mfrow=c(2,6)) apply(Q5,2,hist) myf=function(x){ qqnorm(x);qqline(x) } apply(Q5,2,myf) ########################################## These looks ok. However, I would like to achieve more. Apart from using a loop, is there are fast way to 'add' the titles to be

Hello alltogether, how is it possible to assign the colnames of a data.frame to a function called by apply, e.g. for labeling a plot? Example: I want to plot several qqnorm-plots side by side and there should be a maintitle for each qqnorm-plot which is identical to the respective colname. I checked, but the column which is processed by the function called by apply does not contain a colname

Hi, people. xy.coords() does not behave like its documentation says, when given some matrices. ?xy.coords says: If 'y' is 'NULL' and 'x' is a [...] formula [...] list [...] time series [...] matrix with two columns [...] In any other case, the 'x' argument is coerced to a vector and returned as *y* component [...] Now, consider this short

I've looked around and I just can't find anything that will work for my needs. This is a bit of a 2 part question but pertaining to the same topic so bare with me. The first is with my qq plot. On the Y axis of my qq plot it'll have my sample quantities but because my data is log-normal it'll show numbers between 0 - 5 (depending on the data). I'd like to know how to get it,

The following code was adapted from an example Vincent Zoonekynd gave on his web site http://zoonek2.free.fr/UNIX/48_R/03.html: n <- 1000 x <- rnorm(n) qqnorm(x) qqline(x, col="red") op <- par(fig=c(.02,.5,.5,.98), new=TRUE) hist(x, probability=T, col="light blue", xlab="", ylab="", main="", axes=F) lines(density(x),

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

Tu fichero tiene los decimales como puntos y no como comas como tu le indicas. Te dejo un ejemplo #--------------------------------------------------------------------------------------------------------------------- setwd(dir="c:/Users/usuario/Desktop/") library(outliers) filename<-"timediff.csv" time<-read.csv(filename, sep=";",header=TRUE,dec=".")