similar to: difference between qnorm and qqnorm

Dear R users, I have weekly data in the following manner [,1] [,2] [,3] [,4] 6 2 2 2 5 4 4 3 6 35 2 13 7 32 3 5 4 4 423 3 3 6 4 5 5 6 5 3 I drew curve of each column against days (1,2,3,4,5,6,7). Now I want to draw an average curve (a representative curve) of the whole data. Is there a way in R to perform such operation? please reply ASAP as i have an assignment to submit on monday. Thanks

Dear list-reader, by running the following script: library(zoo) sessionInfo() search() packageDescription("zoo") data(EuStockMarkets) dax <- as.zoo(EuStockMarkets[1:10, "DAX"]) daxr <- diff(log(dax)) identical(as.vector(qnorm(daxr)), qnorm(coredata(daxr))) qqnorm(coredata(daxr)) qqnorm(daxr) qqnorm() produces an error: > qqnorm(daxr) Fehler in if (xi == xj) 0L

--- segue il messaggio inoltrato (the forwarded message follows) --- -------------- next part -------------- An embedded message was scrubbed... From: "QAMAR MUHAMMAD UZAIR" <d029307 at polito.it> Subject: help needed Date: Thu, 24 May 2012 18:36:30 +0200 Size: 1289 URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120524/cad7d73b/attachment.mht>

Do you know of a reference that discusses alternative choices for plotting positions for a normal probability plot? The documentation for qqnorm says it calls ppoints, which returns qnorm((1:m-a)/(m+1-2*a)) with "a" = ifelse(n<=10, 3/8, 1/2)? The help pages for qqnorm and ppoints just refer to Becker, Chambers and Wilks (1988) The New S Language (Wadsworth & Brooks/Cole),

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

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

Hi- I wanted percentage labels on a qqnorm x axis. I used the following: #make up some data jt<-rnorm(100) #qqnorm with percentile x labels qqnorm(jt,axes=F,xlab="Percentiles") box() l<-c(1,5,10,30,50,70,90,95,99) axis(1,at=qnorm(l/100),label=l) which was ok for this data set. Does anyone have a more general solution which would allow one to specify the number of x labels

I found the following strange behavior using qnorm() and pnorm(): > x<-8.21;x-qnorm(pnorm(x)) [1] 0.0004638484 > x<-8.22;x-qnorm(pnorm(x)) [1] 0.01046385 > x<-8.23;x-qnorm(pnorm(x)) [1] 0.02046385 > x<-8.24;x-qnorm(pnorm(x)) [1] 0.03046385 > x<-8.25;x-qnorm(pnorm(x)) [1] 0.04046385 > x<-8.26;x-qnorm(pnorm(x)) [1] 0.05046385 > x<-8.27;x-qnorm(pnorm(x))

Referring to "Using R for Data Analysis and Graphics" by J H Maindonald, and available from the R site, I found the example on p.30 non-working: > stem(qqnorm(possum$hdlngth)) Error in stem(qqnorm(possum$hdlngth)) : 'x' must be numeric Since qqnorm(possum$hdlngth) plots, and > class(possum$hdlngth) [1] "numeric" , the problem must be here: >

I want to qqnorm every column in a table. When I try the first column using qqnorm(table$column1), it worked. But when I use qqnorm(table[1]), it tells me "Error in stripchart(x1, ...) : invalid plotting method". What happen? How can I make a function that qqnorms every column? thanks a lot. -jiong The email message (and any attachments) is for the sole use of the intended

I know this topic has had plenty of discussion in the last couple of days, but.... I've been trying to compare the effects of different fitted methods for systems of equations (OLS, SUR, 2SLS, 3SLS ) and would like to compare the residual plots (easy) and the qqnorm/qqplot of the fits for the different fitted methdos. For example, qqnorm( residuals( lm( q ~ p + f + a ) ) ) par( new = TRUE )

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

Dear List, invoking qqnorm-plots in Version 63.3 produces funny things: using the option `type="s"´ on qqnorm should give a nice *line* of observed quantiles. Now, the line is walking along in order to the points index instead from lowest to highest, wich makes funny slopes. try x <- table(rnorm(1000) # or similar and qqnorm(x,type="s") # in 0.63.2 and 63.3 Well, the

Hello, I am trying to do some plotting to check random effect assumptions for a model I fit using lme. I want to use qqnorm and pairs (similarly to examples given in Pinheiro & Bates p. 188), but it's not working. Here's some relevant code and the error message: library(nlme) data(Machines) m1 <- lme(fixed=score~Machine,random=~1|Worker/Machine, data=Machines) qqnorm(m1,

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

Hello All I am looking for high precision values for the normal distribution in the tail,(1e-10 and 1 - 1e-10) as the R package that I am using sets any number which is out of this range to these values and then calls the qnorm and qt function. What I have noticed is that the qnorm implementation in R is not symmetric when looking at the tails. This is quite surprising to me, as it is well known

Hi all, Does anyone know how to plot overlapping qqnorm plots on the same window? Suppose I have data in the vector x and y: qqnorm(x) lines(qqnorm(y)) I though these two lines will do the job... However, lines doesn't seem to work. Anyways, thanks in advance! -- View this message in context: http://www.nabble.com/Plotting-two-qqnorm-plots%3A-tp25352893p25352893.html Sent from the R help

Hi all, I have just started using R to produce qqnorm plots. I am trying to switch the x and y axes so that the theoretical values are plotted on the y axis and my data on the x axis. Can anyone help me with this? Thanks -- View this message in context: http://www.nabble.com/Flipping-axes-of-qqnorm-tp23248007p23248007.html Sent from the R help mailing list archive at Nabble.com.

how R implement qnorm() I wonder anyone knows the mathematical process that R calculated the quantile? The reason I asked is soly by curiosity. I know the probability of a normal distribution is calculated through integrate the Gaussian function, which can be implemented easily (see code), while the calculation of quantile (or Zα) in R is a bit confusing as it requires inverse error function (X

# I can not draw a 45 degree line on a qqnorm() plot, jj <- sample(c(1:100), 10) qqnorm(jj) abline() don't work. Thank you.