similar to: QQ plot for normality testing

hi all, I have a plot to which i would like to add text labels. And i cant find a way...here is the code : enaD2<-idw(D2~1, loca=dva, newdata=grd) pts = list("sp.points", dva, pch = 20, cex=1.5, col = "darkred spplot(enaD2, "var1.pred",sp.layout=pts, main = "globina 60 cm", sub="D2",

Hi all, I would like to create a scatter plot of two variables (y, x) whith third value (z) written on the plot? After that i would like to add a line (Y=0.7*(x-20)) to the graph. I tried plot(x~y) but there is no command for the third vairable to be shown on the graph also i can't find a way to add a Y=x*(0.7-20) to the chart. Thanks, m [[alternative HTML version

Hi, Is it possible (i am sure it is) to subset data from a data.frame on the basis of SQL >LIKE< operator. I.e., i would like to subset a data where only values which contains a string >GP< would be used? Example: Gp<-subset(DF, DF$USCS like >GP<) This like of course is not working, Thanks, m [[alternative HTML version deleted]]

Hi all, i have a data set cintaining 14 columns and 11 rows. Rows represent single point and columns represent the parameter measured. I wiuld like to compare the data to see which are more alike. I used the cluster analysis, but now i ma wondering if there are some other methods, since the cluster analysis did not give me the result i like. I tried to use factanal() for factor analysis

Hi all, I got the >"chfactor.c", line 130: singular matrix in function LDLfactor() Error in predict.gstat(g, newdata = newdata, block = block, nsim = nsim, : LDLfactor< Error, probably because there are some point pairs with zero distance in the matrix. My question is, how can i delete these duplicate nodes from the data set? Thanks, m [[alternative

I'm new to R (and to S) and am wondering about code from pages 72 and 83 of MASS (Venables+Ripley, 3rd edition), to draw an envelope on a QQ plot. Copying from the book, I've got: #... code whose gist is "a.fit <- nls(..." num.points <- length(resid(a.fit)) qqnorm(residuals(a.fit)) # illustrate data-model residuals qqline(residuals(a.fit)) samp <-

Hi Steven, Thank you for the help. I get an error though when i do this : >lit<-read.csv("litologija.csv", sep=";", dec=".") >sent <-data.frame(sentence=lit$Opis,stringsAsFactors=FALSE) >str(sent) >sentV<-rep(sent,10) >str(sentV) >first=second=third=fourth=fifth=sixth=seventh=eighth=ninth=tenth<-vector(length=10) >DF

Hi all, Is there a way to pass R code from web page (html file) to do some statistics and than plot the output in web browser. I am looking forever at this, and cant find a way. Regards,m -- View this message in context: http://r.789695.n4.nabble.com/Passing-R-code-from-webpage-tp4658800.html Sent from the R devel mailing list archive at Nabble.com.

Good Morning: I have attached a text file with one hundred thirty six observations. I would like to create a qq plot with the following features: 1. Observed values on the y-axis. 2. Normal approximation line on the plot. 3. X-axis with vertical reference lines at the following percentiles of the data: 1, 10, 20, 50, 80, 90 and 99. 4. Data appearing on the plot as distinct points. I assume that

Hi, R friends. I had some difficulty with the following code: qqnorm(freq, log='y') qqline(freq) as the line drawn was seemingly random. The exact data I used appears below. After wandering a bit within the source code for "abline", I figured out I should rather write: qqnorm(freq, log='y') par(ylog=FALSE) qqline(log10(freq)) par(ylog=TRUE)

I have 20 variables: 5,9,6,1,5,9,7,4,5,6,3,2,4,8,9,6,1,8,4,8 How do I calculate the corresponding quantiles from a normal distribution with the same mean and variance as the sample? Also, how do I draw a QQ plot of the data? Thanks for any help! -- View this message in context: http://www.nabble.com/Quantiles-and-QQ-plots-tf4925742.html#a14097909 Sent from the R help mailing list archive at

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|

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

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

# 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.

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

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 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

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