similar to: (x,y) coordinates for grid.text()

All, How does one replace plot symbols with say subject IDs when using xyplot? Or superimpose them next to plot symbols? I searched the archives under various key words but haven't had much. Any suggestions or links much appreciated. Sample code below. David junk.frm = data.frame(ID = rep(1:16, each = 2), x, y, z = rep(c("D", "P"), 16)) y = c( 0.4, 0.6, -0.1,

All, I'm having problems w/ a simple attempt to subset an xyplot. The first plot below is a plot of y versus x for certain values of a third categorical variable z. Now I'd like to further restrict this to certain values of variable y. Neither of the two attempts below work. Any suggestions much appreciated. (note: I don't want to merely use ylim since I have a loess plot and I

Dear R help, I have some readings in three dimensions (x, y, z) and an amplitude for each. I'd like to visualize the data using ggplot, using tile plots, as I have some additional point data I would like to eventually overlay on the tile plots. I would like to subset the data by sections, slices if you will, in the z dimension, and plot the data for that slice. I can do all of this, but am

Dear all, I am stuck with a problem that might be trivial for most of you (and therefore is a bit embarrassing for me...): I want to calculate a generalized least squares regression using two time series (Y depending on X) with an autoregressive correlation structure of order two (the data along time are given below). I use 'gls' from package 'nlme': Calib.gls <- gls(Y~X,

Hi, I have the following data: > Myvalues Gene ES MEF Embryo ESHyp 1 GeneA -0.38509507 0.00 1.6250 1.7039921 2 GeneB 0.06262914 0.00 1.6250 -0.272033 and so on... I want to plot the expression values of GeneA and GeneB in the different cell/embryo/conditions (columns 2:5 above). Now, if I do: >library(ggplot2) > qplot(x=Gene, Embryo, geom =

I just upgraded our optimizer to LLVM 3.0 from 2.8 and noticed that the scalar replacement of aggregates pass takes a lot longer for some code. Has there been a performance regression in this pass, or does it do more work? LLVM 3.0: Total Execution Time: 1.0600 seconds (1.0526 wall clock) ---User Time--- --System Time-- --User+System-- ---Wall Time--- --- Name --- 0.5100

Hi all, I was trying to convert a data frame to a zoo object so I can use some time series functions like lag(). But it seems then everything became a factor, so I have to convert it back to numeric to run the correct regressions. Is there a way to avoid it? Here is an example: ############################# a <- data.frame(nn =as.character(c("a", "b", "c",

Hello R users, I have been using R for a while now for basic stats but I'm now trying to get my head around looping scripts and in some places I am failing! I have a data set with c. 1200 data points on 98 individual animals with data on each row representing a daily measure and I am asking the question "what variables affect the animal's behaviour?" the dataset includes

I have generated the following: x= E1 E2 E3 D1 0 0 1 D2 1 0 3 D3 0 2 0 y= E1 E2 E3 D1 0 0 1.75 D2 1.75 0 1.3125 D3 0 3.5 0 Where x and y are linked by: y =sum(x) * x / (rowSums(x)%o%colSums(x)) N=x[x[1:3,]>0] R=y[y[1:3,]>0] Now suppose I ONLY

Hello, R-folks: Here is a statement I use to make a data frame: iccdata <- data.frame(i=rep(1:10,rep(2,10)),j=rep(1:2,10), x=c(0.35011,0.11989,0.13081,0.09919,0.16000,0.12000,0.00000,0.00000, 0.44023,0.32977,2.67081,2.63919,0.09050,0.03950,0.44019,0.30981,0.59000, 0.57000,4.03000,3.77000)) Then here are the data: > iccdata i j x 1 1 1 0.35011 2 1 2 0.11989 3 2 1 0.13081 4

Hello, Hope that someone could help me plotting longitudinal data below: 7213 3333330001 0.8300 13.05.09 1 1 3333330001 0.8700 09.02.05 NULL 4797 3333330001 0.7700 21.03.07 NULL 2399 3333330001 0.7800 12.04.06 NULL 2400 3333330002 NULL 27.03.06 NULL 7230 3333330002 0.8200 14.05.09 0 2 3333330002 0.8400 09.02.05 NULL 4798 3333330002 0.8700 20.03.07 0 4799 3333330003 0.9000 20.03.07 13 2401

On Jul 24, 2011, at 3:02 AM, Duncan Sands wrote: > A big compile time regression. Any ideas? > > Ciao, Duncan. False alarm. For some reason that I have not yet been able to figure out, these tests run significantly more slowly when I run them during the daytime, which I did for that run. I checked a few of the worst regressions reported here and they all recovered in subsequent

Hello all I'm trying to learn how to fit a nested model in R. I found a toy example on internet where a dataset that have?3 areas and 4 sites within these areas. When I use Minitab to fit a nested model to this data, this is the ANOVA table that I got: Nested ANOVA: y versus areas, sites Analysis of Variance for y Source DF SS MS F P areas 2 4.5000 2.2500

Hi, I have just tagged 3.7.1-rc1, so it is ready for testing. As a reminder, when doing regression testing, use the 3.7.0 release as your baseline. Thanks, Tom

A big compile time regression. Any ideas? Ciao, Duncan. On 22/07/11 19:13, llvm-testresults at cs.uiuc.edu wrote: > > bwilson__llvm-gcc_PROD__i386 nightly tester results > > URL http://llvm.org/perf/db_default/simple/nts/253/ > Nickname bwilson__llvm-gcc_PROD__i386:4 > Name curlew.apple.com > > Run ID Order Start Time End Time > Current 253 0 2011-07-22 16:22:04