similar to: the meaning of subscripts

Hi, I am trying to change a SAS macro to R. here is my code. I get an error at the last line. attach(fram) dset1<-cbind(AGE,BMI,DEATH) > BMIGRP<-cut(BMI,breaks=3,right=TRUE) > AGEGRP<-floor(AGE/10)-2 > dset<-cbind(AGEGRP,BMIGRP,DEATH) > maxage<-max(dset[,1]) > minage<-min(dset[,1]) > #maxcls<-dset[,2] > #mincls<-dset[,2] >

Dear r-help, I need to draw xyplot() graphs with several regression lines: one line for the whole range of x (the variable on the horizontal axis) and two additional lines for subranges of x. Is it possible to make first regression line (panel.lmline(x,y,...);) to be drawn on the whole graph and regression lines of the subsets to be drawn only over their subsets? I have defined

1) I have a data that includes some "bad" data. I want to make a trellis plot where each panel contains a) A scatter plot of the "good" data b) A scatter plot of the "bad" data in a different color c) A best fit line of all the data, and d) A best fit line of the "good" data. I tried using xyplot and setting the "group" argument, but I'm

Hi Dieter and R community: I tried both of these three versions with ylim as suggested, none work: I am getting only single (pch = 16) not overlayed (pch =3) everytime. *vs 1* require(lattice) xyplot(Sepal.Length ~ Sepal.Width | Species , data= iris, panel= function(x, y, subscripts) { panel.xyplot(x, y, pch=16, col = "green4", ylim = c(0, 10)) panel.lmline(x, y, lty=4, col =

I am wanting to generate panels showing scatterplots with the linear fitted line for two groups within each panel superimposed. I have two conditioning factors, "variable" and "Group" and I want separate panels for each level of "variable" with different symbols and "lmline"s for each level of "Group". However all observations for a group are

Hi, is it possible to reverse the order in which panel.lmline() or panel.smooth() operation in xyplot() ? This type of situation might occur when plotting some variable with depth, but the relation we want to describe is variable ~ depth, and not depth ~ variable, as the plotting formula would suggest. # an example: d <- 1:100 v <- d * rnorm(100) xyplot(d ~ v, ylim=c(100,0),

Hi, I am trying to produce an xyplot with a regression line. The data should be represented as log/log but when I fit the lmline I receive an error message - the plot is fine without the log transformation, but the then the plot is meaningless. I know it must be something simple, but I just can't see it. Hope someone can help... Thanks. xyplot(log(Pk)~log(k),data=rwpk,cex=1,

I wish to display a single-panel Lattice figure with grouped data and fitted regression lines. I don't seem to be able to get the individual regression lines to display, e.g.; d <- data.frame(q = rep(1:6, each=10), cc = rep(seq(10,100, 10),6)) # create data frame with group identifier 'q', independent variable cc d$ba = d$q*0.1*d$cc + 5*rnorm(nrow(d))

panel.lmline returns intercept and slope of y ~ x subsetted to the combination of conditioning factors given to xyplot in lattice. for instance: xyplot(Xvalues ~ log(Qvalues)|Tfac, data = df7, panel = panel.lmline) I am looking to find the equivalent formulation for lm() proper. If I do this: lmcal <- lm(Xvalues ~ log(Qvalues):Tfac, data = df7) Only one value of the intercept is returned.

Dear list, I want to plot several variables with splom and in the main diagonal, instead of the variable names, I'd like to plot an histogram of corresponding variables. Searching I did not find the correct syntax, only some tips in an old post in the list, but this comments help to plot only density lines instead of histograms. I had some code, but it fails to plot (I've commented the

R 2.8.1 Windows XP I am trying to plot the results of a coxph using plot(survfit()). The plot should, I believe, show two lines one for survival in each of two treatment (Drug) groups, however my plot shows only one line. What am I doing wrong? My code is reproduced below, my figure is attached to this EMail message. John > #Create simple survival object >

In the HistData package, I have a data frame, PearsonLee, containing observations on heights of parent and child, in weighted form: library(HistData) > str(PearsonLee) 'data.frame': 746 obs. of 6 variables: $ child : num 59.5 59.5 59.5 60.5 60.5 61.5 61.5 61.5 61.5 61.5 ... $ parent : num 62.5 63.5 64.5 62.5 66.5 59.5 60.5 62.5 63.5 64.5 ... $ frequency: num 0.5 0.5

How do you get the design matrix R used when calculating ANOVA? -- View this message in context: http://www.nabble.com/how-to-get-design-matrix--tp23464638p23464638.html Sent from the R help mailing list archive at Nabble.com.

Dear R Users, I have an xyplot() where different plotting symbols are used for subgroups (originally used within S-Plus, but hopefully it?s also applicable to R users). How can I fit separate regression lines for every subgroup? So far, I can only plot the overall fitted line. The code looks like this: trellis.device() sps<-trellis.par.get("superpose.symbol") sps$pch<-1:7

Page 140 of MASS uses the function xyplot. But I don't find it in R. Is there a package that I should load to use xyplot. Or there is a function with a different name in R that does the same thing as xyplot in S. xyplot(Gas ~ Temp | Insul, whiteside, panel = function(x, y, ...) { panel.xyplot(x, y, ...) panel.lmline(x, y, ...) }, xlab = "Average external temperature (deg. C)", ylab

I am interested to use plotmath functions within a panel function but am having some problems getting the code right. Within each panel I am plotting the data, fitting a regression line, and would like to print the regression equation. Here is a trivial example of what I'd like to do: # generate simple data tmp.df <- data.frame(id = rep(1:4, each=4), time = rep(1:4, 4), das =

Hi Folks, I have just started using dplyr and could use some help getting unstuck. It could well be that dplyr is not the package to be using, but let me just pose the question and seek your advice. Here is my basic data frame. head(h) subject ageGrp ear hearingGrp sex freq L2 Ldp Phidp NF SNR 1 HALAF032 A L A F 2 0 -23.54459 55.56005 -43.08282

Does identify work in lattice plots? I tried this in R 1.4.1 (original release) on my Win2000 machine with lattice 0.4-0 and grid 0.5-1. > xyplot(y ~ x, + panel=function(x, y, ...){ + panel.xyplot(x, y, col=2, pch=20, ...) + panel.lmline(x, y, type = "l") + identify(x, y) + }) I get a change of cursor after the data points and the LS line are plotted

I have data that looks like this: start end value 1 4 2 5 8 1 9 10 0 I want to transform the data so that it becomes: startend value 1 2 2 2 3 2 4 2 5 1 6 1 7 1 8 1 9 0 10 0 ---- I've

Dear list Maybe someone can help with the following problem: I have a source file containing the following code for plotting: pdf(file = 'data/mario/boxplot.pdf') bwplot(sig100 ~ target | group, data = fish, main = 'Boxplot der Signale in 100 Zellen nach Gruppe', xlab = '', ylab = 'Anzahl der Signale') dev.off() pdf(file = 'data/mario/xyplot.pdf')