similar to: "symbol print-name too long"

All, I have a repeated measures data frame and was wondering if the covariance matrix can be calculated via some created indexing or built-in R function. Specifically, say there are 3 variables, where potassium concentration is measured 6 times on each patient. Patient number (discrete) Time (1 to 6, discrete) Potassium (continuous variable) I want the covariance/correlation matrix for the

All, I'm trying to create an augPred plot in the nlme library, similar to the plot on p.43 of Pinheiro & Bates (Mixed Effects Models in S and S-Plus) for their Pixel data. My data structure is the same as the example but I still get the error msg below. > comp.adj.UKV <- groupedData(adj.UKV ~ Time | Patient_no/Lisinopril, data = comp.adj.UKV.frm, order.groups = F) >

Dear R list, I have a sequence of weekly observations of number of adults and larvae in various size classes from a butterfly population living in a subtropical area with pronounced wet and dry seasons. Wet and dry seasons are each defined 26 weeks long with fixed start and end dates. The data span 103 weeks (two seasons each of wet and dry) with some missing weeks. What I would like to do is

Dear R Help, I've just installed 1.7.1 and have found that the console now exhibits odd behavior when I paste commands into it. I'm on a PC running Windows XP Professional. I use Word as my script editor, and then paste commands into the R console using the standard Windows "copy" within Word then "paste" within Rgui. This worked without a hitch in 1.7.0, but now in

I need advice on how to create a variable that is the group mean of another variable. For example, I have a variable called x for which each row in the data set has a value. I also have a nominal variable called g that indicates which of 100 different groups each row belongs to. So, I want to create a new variable called w, which is the group mean of x for which ever group the row belongs to (as

I used the following to assign each row the group average, where w is the new group average variable, x is the variabale to be averaged, and g is the nominal group indicator: w <- ave(x,g) Now I want to calculate the group average, but WITHOUT each row's value of x. Is there an easy way to do this? I'm sure I'm missing something obvious here, but for the life of me I can't

I'm sure this is easy, but I'm having a hard time figuring out how to recode some data in R. I have a variable "numpeers" which is valued 1, 2, or 3. I also have three other variables called "w9zd9_1," "w9zd9_2," and "w9zd9_3." I want to use these variables to create a new item called "distot." Specifically, here is what I want to do:

All, I'm trying to make a basic plot: data points superimposed upon the a line connecting the points w/ a different color. Example below doesn't work as the first xyplot call doesn't remain. Suggestions? David Hour = c(NA,1,2,3,4) y = c(2,2,3,2,1.5) xyplot(y ~ Hour, xlab = list("Hour", font=2, cex=2), ylab= list("U_x * V", font=2, cex=2), type = 'l',

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, Sorry for overly simplistic question, but I can't seem to remember how to create the basic plot shown in Figure 1.1 of Pinheiro & Bates (2004; p.4). The y-axis delineates a factor (Rail) while the x-axis displays the distribution of a continuous variable (time) according to each level of the factor. Didn't see it in archives but perhaps I'm not searching on correct key words,

All, I have data across 5 time points that I am graphing via xyplot, along with error bars. For one of the variables I have missing data for two of the time points. The code below is okay but I can't seem to get the lines to connect across the missing time points. Does anyone now how to rectify this? Cheers, David Afshartous library(lattice) ## the data junk = data.frame( Visit =

All, The code below produces a color 3D graph. I'd like to make it black and white shading. I tried setting col.regions to FALSE but this just made it completely white. I want the graph to look exactly as is, except black (or grey) and white shading. Is this possible? Cheers, David p.list = c(.01, .1, .25, .5, .75, .9) cov.list = c(.2, .1, .05) ### leave out .01 X = rep(p.list, 3)

All, I have a simple lattice plot where I have set log = TRUE for the y scale. When I attempt to change the tick locations via the "at" argument within scales, the supplied numeric vector is not followed. Any suggestions much appreciated for the example below: y = c(10^1.5, 10^2, 10^3, 10^2) t = c(1,2,3,4) xyplot(y ~ t, type = "b", scales = list(y = list(log = TRUE))) ##

All, Below is an xyplot plot with multiple panels and a title produced via main: library("lattic") data.ex = data.frame(y = rnorm(10), t = rep(1:5, 2), group = rep(c(0,1), each = 5)) xyplot(y ~ t | as.factor(group), data = data.ex, main = list("Put figure caption here xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx want this line left justified" )) I must be mis-interpreting the

All, I'm witnessing some strange behavior when checking the values of one of my variables. My guess is that it has something to do with the number of significant digits being represented, but perhaps not as my variable was created from other variables that only had one decimal place. See below. I'm sure this is something basic, any suggestions much appreciated. Cheers, David >

All, On p.52 of Deepayan Sarkar's Lattice book there is a nice plot of showing residuals with median lines superimposed or various groups: library("lattice") stripplot(sqrt(abs(residuals(lm(yield~variety+year+site)))) ~ site, data = barley, groups = year, jitter.data = TRUE, type = c("p", "a"), fun = median) Suppose we wanted to make a similar plot for a

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

So, I've finally gotten around to installing a Samba4 AD DC. I've joined a Win7 and Ubuntu machine to the domain so far, and all works perfectly. Great job guys, it's nice to see this functionality working solidly on Samba! The problem is coming in on the actual DC host. My Ubuntu laptop is running winbindd 3.6.18, and as I said, all went flawlessly. The DC host is running

All, When I take a subset of a factor the reduced factor still maintains all the original levels of the factor when say forming the key in a plot. The data is correct, but the variable still "remembers" the original levels. See below for reproducible code. Does anyone know how to fix this? cheers, dave fact = as.factor(c(rep("A", 3),rep("B", 3), rep("C",

All, I'd like to plot the main relationship of a grouped data object for all levels of a factor in a single panel. The sample code below creates a separate panel for each level of the factor. I realize that this could be done in other ways, but I'd like to do it via plotting the grouped data object. thanks! dave z = rnorm(18, mean=0, sd=1) x = rep(1:6, 3) y =