similar to: use of 'apply' for 'hist'

=========================== myf=function(ds=1){ x=rnorm(10) y=rnorm(10) { #start of if if (ds==1) { list(x,y) } else (ds==2) { plot(x,y) } } # end of if } # end of function =========================== Hi All, the problem i am having here is, that I want to be able to control the display, lf ds=1, i want to just have a list, but it seem to always plot... Thanks. casper -- View this

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 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

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

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 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

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

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 all, Is there any other packages to do numerical integration other than the default 'integrate'? Basically, I am integrating: integrate(function(x) dnorm(x,mu,sigma)/(1+exp(-x)),-Inf,Inf)$value The integration is ok provided sigma is >0. However, when mu=-1.645074 and sigma=17535.26 It stopped working. On the other hand, Maple gives me a value of 0.5005299403. It is an

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),

Hello Everyone Both the MCMCpack and the bayesm libraries allow us to make draws from the Inverse Wishart distribution. But I wanted to find out how exactly is the Inverse Wishart distribution parameterized in these libraries. The reason I ask is the following: Now its generally standard to express Inverse Wishart as IW(0.5 * DOF,0.5* Scale). (DOF-> Degree of freedom, Scale -> Scale

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]]

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,

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'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 <-