similar to: lattice: reverse order of panel.lmline, panel.smooth

Hi, I was recently splitting some massive phylo class objects with extract.clade() and noticed what appears to be a bug in how tip labels are copied from the full tree to the pruned tree. This possible bug was also mentioned here: http://www.mail-archive.com/r-sig-phylo at r-project.org/msg00537.html An example: library(ape) set.seed(5) x <- matrix(rnorm(100), ncol=10) p <-

Hi, I have been trying to use the new .parallel argument with the most recent version of plyr [1] to speed up some tasks. I can run the example in the NEWS file [1], and it seems to be working correctly. However, R will only use a single core when I try to apply this same approach with ddply(). 1. http://cran.r-project.org/web/packages/plyr/NEWS Watching my CPUs I see that in both cases

Hi, I am trying to transition a system based on dynamic image generation (via R) from our development system to a production environment. Our R script functions as expected when run by a regular user. However the script dies when calling the png() function, when started by the webserver user. Here are some details >sessionInfo() R version 2.9.2 (2009-08-24) i686-pc-linux-gnu locale: C

Hi, I have fit a series of ols() models, by group, in this manner: l <- ols(y ~ rcs(x, 4)) ... where the series of 'x' values in each group is the same, however knots are not always identical between groups. The result is a table of 'coefs' derived from the ols objects, by group: group Intercept top top' top'' 1 6.864 0.01 2.241 -2.65

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

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

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.

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,

Dear Sebastian Luque (and All R Users) With the following code I managed to plot different characters and regression lines for panels 2 ("Day of year 101") and >4 ("Days of year" 151, 157 and 172): xyplot(log(no.larvae)~age.cls|factor(day),data=mortal, layout=c(7,1),aspect=5/3, xlab="Age class (d)",ylab="Ln(Abundance)",

Dear All, I'm confortable with xyplot(...) and panel.lmline(...) statements (at least I thought I did :). I've used the following code to plot the decline in log-abundance of fish larvae (no.larvae) with age (age.cls, 4 to 27 days-old) for specific dates of sampling (day, 9 dates). I further plotted data with different colors and regression lines for ages 5-14 d and 17-23 d in a 7-by-1

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

Hi, Is anyone on the list familiar with an R implementation of Piper Diagrams? Example: http://faculty.uml.edu/nelson_eby/89.315/IMAGES/Figure%209-78.jpg I am thinking that two calls to triax.plot (plotrix) along with some kind of affine-transformed standard plot would do the trick. Not so sure about the final layout, or a nice generalized version for something like lattice. Cheers, Dylan

Hi, Is there a simple way to suppress the plotting of polygon boundaries with spplot() ? # simple list of 12 colors cols <- brewer.pal(12, "Paired") # plot pile of polygons, with 12 classes: spplot(x, zcol='class2', col.regions=cols, scales=list(draw=T), xlab="Easting (m)", ylab="Northing (m)") ... seems to work well. However the polygon boundaries

Hi, Is there any way to suppress plotting of panels that don't actually contain any information? I have tried using 'drop.unused.levels=TRUE', but there doesn't seem to be any effect. Here is an example: library(lattice) # some fake data: d <- data.frame(x=runif(20), x.class=rep(letters[1:5], each=4), f1=rep(letters[1:2], each=10), f2=rep(letters[10:19], each=2) ) # plot

Hi R Folks... Are the results of a fit carried out by panel.lmline readily available for use in a lattice plot? I¹d like to put r^2, m, and b on each panel. I can certainly write something that does this manually and then use it with panel.text, but if it¹s already available, that would be preferable, especially as lattice permits condition and subsetting so readily. Looking at panel.abline, I

Hi, I have fit a model using the rms package with the Gls() function. Is there a way to get the model estimates, std errors, and p-values (i.e. what you get with print(fit)) into latex format? I have tried: f <- Gls(...) latex(f, file='') ... but I get the following error Error in replace.substring.wild(s, old, new, test = test, front = front, : does not handle > 1 * in

Hi, I am curious about how to interpret the results of a polynomial regression-- using poly(raw=TRUE) vs. poly(raw=FALSE). set.seed(123456) x <- rnorm(100) y <- jitter(1*x + 2*x^2 + 3*x^3 , 250) plot(y ~ x) l.poly <- lm(y ~ poly(x, 3)) l.poly.raw <- lm(y ~ poly(x, 3, raw=TRUE)) s <- seq(-3, 3, by=0.1) lines(s, predict(l.poly, data.frame(x=s)), col=1) lines(s,

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))

Hi, How would one go about determining if the slope terms from an analysis of covariance model are different from eachother? Based on the example from MASS: library(MASS) # parallel slope model l.para <- lm(Temp ~ Gas + Insul, data=whiteside) # multiple slope model l.mult <- lm(Temp ~ Insul/Gas -1, data=whiteside) # compare nested models: anova(l.para, l.mult) Analysis of Variance

Hi, Running the following example from ?Predict() throws an error I have never seen before: set.seed(1) x1 <- runif(300) x2 <- runif(300) ddist <- datadist(x1,x2); options(datadist='ddist') y <- exp(x1+ x2 - 1 + rnorm(300)) f <- ols(log(y) ~ pol(x1,2) + x2) p1 <- Predict(f, x1=., conf.type='mean') Error in paste(nmc[i], "=", if (is.numeric(x))