similar to: (Novice-) Problem with the plot-function

Hello list ! I have a huge data.frame with several variables observed on about 3000 persons. For every person (row) there is variable called GROUP which indices the group the person belongs to. There is also another variable AV for each person. Now i want to create a new variable which holds the group mean of AV as a value for each person. With tapply(AV,GROUP,mean) i get the means for each

Dear list, I asked some questions about multilevelanalysis a couple of months ago. In the meantime I did some reading about the subject. Now I'd like to check, if I understood it all correctly. If you think my questions are not appropriate for this list, please tell me so and i will immediatly stop asking them. I have a dataset with one predicted variable (y), two explanatory variables

Dear list, i am a student of psychology and have to do a multilevelanalysis on some data. About that i have one general and one specific question. This is what i have copied from the help-file on lme: data(bdf) fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR) summary(fm) after summary(fm) i get the following error:

Hey Felix, So basically what you want is a figure containing a block of four plots, with a main title for the figure? If that's the case then something like this should work: # BEGIN CODE # par(oma=c(0,0,1,0), mfrow=c(2,2)) for(i in 1:4){ plot(NA,xlim=range(0,10),ylim=range(-5,5)) title(paste("Plot ",i,sep="")) } par(mfrow=c(1,1), oma=c(0,0,1,0)) mtext("Main

Hi, I'm trying to find the maximum (likelihood) of a function. Therefore, I'm trying to minimize the negative likelihood function: # params: vector containing values of mu and sigma # params[1] - mu, params[2]- sigma # dat: matrix of data pairs y_i and s_i # dat[,1] - column of y_i , dat[,2] column of s_i negll <- function(params,dat,constant=0) { for(i in 1:length(dat[,1])) {

Hi All, Did anyone else have a problem like this? I am sorry if its a small issue, I seem to not understand what to do to get rid of this error. > Sigma [1] 0.1939025 > MuRest [1] 8.512772 > TauZero [1] 0.1 > curve(qlnorm(x,-TauZero+MuRest, Sigma,lower.tail=F), xlim=c(4000,9000), ylim=c(0,.99),xlab="", ylab="") Warning message: In qlnorm(p, meanlog, sdlog,

Hello, I would appreciate if someone could help me with this query. I would like to plot a line chart of all of the points in a "for" loop. I would also like to plot the final point with a symbol (to show where the random walk ends). Here is the code I am using: Brownian.fn <- function(mu, sigma, T, N){ dt <- T/N t <- c(rep(NA, N)) B1 <- c(rep(NA, N)) B2 <- c(rep(NA,

I have an instance where I need to include Greek letters on a plot title that is multiple lines. ? I've searched the forums for an approach to do this, but most of the previous posts and replies seem to just address instances of single line examples and problems:, e.g. ? https://stat.ethz.ch/pipermail/r-help/1999-October/005096.html ? I tried implementing those suggestions, e.g.

I thought the curve function was a very flexible way to draw functions. So I could plot funtions like the following: # I created a function to produce functions, for instance: fp <- function(m,b) function(x) sin(x) + m*x + b # So I can produce a function like this ff <- fp(-0.08, 0.2) ff(1.5) # Is the same as executing sin(1.5) - 0.08*1.5 + 0.2 # Let's plot this

This is a followup to a recent post on using atop() to obtain multiline expressions. My reading of the plotmath docs makes it clear that issuing (in base graphics) the specification par(cex = 2) doubles symbols and regular text in subsequent plotmath expressions. However, it is unclear to me what specifying cex _within_ the annotation function using plotmath should do, and the following seems

Hi, I have got four correlation matrix. They are the same set of variables under different conditions. Is there a way to test whether the correlation matrix are significently different among each other? Could anyone give me some advice? -- View this message in context: http://www.nabble.com/correlation-matrix-difference-tf4073868.html#a11578046 Sent from the R help mailing list archive at

Hi dear list, I'm scrambling with this: i have a p-dimensional data frame for which i want to have a pairs() plot, with ellipse added in each lower.panel. I want the ellipse's parameter (mu, sigma) to be extracted from the appropriate entries in a pre-computed matrix ("dab" in the code below). Can it be done ? Thanks in advance, melly<-function (x, y, col =

Dear All, I'd like to fit a "kind" of logistic model to small data-set using nonlinear least-squares regression. A transcript of R-script are reproduced below. Estimated B and T (the model's coeff, herein B=-8,50 and T=5,46) seem appropriate (at least visually) but are quite diff from those obtained w/ SPSS (Levenberg-Marquardt): B=-19,56 and T=2,37. Am I doing something wrong in

Hi, I have a question about exporting interactive 3D plots. I use the following code to plot a contour of a trivariate normal distribution: library(mvtnorm) library(rgl) library(misc3d) n=25 x=seq(-3,3,length=n) X=cbind(rep(x,each=n**2),rep(rep(x,each=n),n),rep(x,n**2)) p=array(dmvnorm(X,sigma=diag(3)*0.5+0.5),c(n,n,n)) contour3d(p,x,x,x,level=mean(p)) lim=c(-3,3)

Dear list, I am looking for a possibility to present results in a more graphical way by adding an axis. But I have trouble relating my data to the added axis. Imagine the following example: a <- c(10, 20, 30, 40) b <- c(50, 250, 500, 600) ba <- b/a par(las=1, mar=c(5,5,.5,5)) plot(a,b, type="b", pch=22, cex=2, col=4, lwd=2, ylim=c(0,650), xlim=c(0,45)) axis(4,

Hi: Is there a way to get smoothScatter to not clip when I increase the xlim and ylim parameters? Consider the following example: set.seed(17) x1<-rnorm(100) x2<-rnorm(100) smoothScatter(x1,x2) #Now if I increase xlim and ylim notice that the plot seems to be clipped at the former xlim, and ylim boundaries: smoothScatter(x1,x2, xlim=c(-5,5), ylim=c(-5,5)) Thanks. Jen sessionInfo() R

hello everyone, i am getting problems in graph plotting. When i attach file after adding color attributes in my data set. i got problem of "GlobalEnv" and masked the followings. Like this >attach(machm) The following object(s) are masked _by_ '.GlobalEnv': coll, sp The following object(s) are masked from 'mach': angle, area, dis, plot, sp

list(...), I would like to zoom in to the leaves of large trees in a dendrogram plot. The playwith package allows zooming by passing xlim and ylim arguments to the plot call (Hmisc does this too I think). But currently stats:::plot.dendrogram does not accept xlim or ylim. So I would like to enable that. In place of the existing code chunk: xlim <- c(x1 - 1/2, x2 + 1/2) ylim <- c(0,

Dear R users, I’m trying to understand how correlated predictors impact the Relative Importance measure in Stochastic Boosting Trees (J. Friedman). As Friedman described “ …with single decision trees (referring to Brieman’s CART algorithm), the relative importance measure is augmented by a strategy involving surrogate splits intended to uncover the masking of influential variables by others

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file: