similar to: appending

sent this to the list yesterday but didn't see it listed in the daily summary ... apologies if you receive it twice ... ________________________________ From: Afshartous, David Sent: Tuesday, June 27, 2006 10:02 AM To: 'r-help@stat.math.ethz.ch' Subject: sapply question All: I'm trying to use sapply to break up data within another function. (tapply doens't seem to work

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) >

All, When saving plots to a pdf file via the pdf function, I would like to be able to automatically expand the graphics device to achieve the same result as when one does this manually (e.g., clicking the green expand button on the upper left of the graph on Mac OS). Consider simple example below: library("lattice") foo.frm = data.frame(Subject = rep(c(1:4), each = 9), Y =

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

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,

Using the Cement hardening data in Anderson (2008) Model Based Inference in the Life Sciences. A Primer on Evidence, and working with the best model which is lm ( y ~ x1 + x2, data = cement ) the AIC value from R is model <- lm ( formula = y ~ x1 + x2 , data = cement ) AIC ( model ) 64.312 which can be converted to AICc by adding the bias

I am still searching for a solution to what i think is a simple problem i am having with building a vector in a for loop. I have built a more understandable example so hopefully that will help..help you, help me, if you know what i mean. dev=400 #test location model TAZs to reference cands=c(101,105,109) #Create Object of length of cands candslength=length(cands) #TEST TAZ Vector

Hello, This is a question motivated by curiosity, not a pressing problem. Any responses are much appreciated! In the following code, function reg1 calls glm with a formula object while reg2 uses a string. In both cases, glm works; however, in the second case, the add1 function fails with the following message: "Error in eval(predvars, data, env) : invalid 'envir' argument."

Hello all, I have matrices V.i of dimension n.i x n.i, where i = 1, ..., J, and the sum of n.i equals N. (and n.i ! = n.j) goal: create one large matrix V, where V has matrices V.i on diagonal. I create each matrix V.i in a for loop (1 to J), so each time I'd like to augment V with the most recently calculated V.i, such that I'll have V after the final iteration of the for loop.

Hello all, X is a list of 20 lists, and each individual list has 65 elements. Y is a list of 65 elements. WANT: subtract Y from each of the 20 lists in X. Here's what I tried and the error messages: > X - rep(Y, 20) Error in X - rep(Y 20) : non-numeric argument to binary operator I tried several methods w/o success. Any suggestions kindly appreciated. Thanks, Dave ps - please copy

All, For data consisting of serial measurements on subjects, one may use the aggregate function to say compute the peak response for each subject for each design condition. Is there a way to alter this or another one-liner to also retain the time at which the peak occurred and thus avoid writing a doing this via a loop? I suppose one could attempt to employ the split function but that's

All, Is there are a wildcard in R for varible names as in unix? For example, rm(results*) to remove all variable or function names that begin w/ "results"? cheers, Dave ps - please respond directly to afshar@miami.edu [[alternative HTML version deleted]]

All, When starting R, how does one prevent the loading the previous workspace which was saved? I'd like to start a new project and save the new image in a different directory, but I'd like to partition this from the old project. Does there exist a better way than just deleting the files associated w/ the old project manually? I looked in the Intro to R manual and searched for

All, Usually when I save a variable I have ascii = FALSE since I usually load the variable via the load(variable) command and do not need to view the variable outside of R. When I set ascii = TRUE and view the variable outside of R in a text editor, I notice additional characters (starting w/ RDA2 ...) before the first actual value in the vector. Is there are way to save to ascii such that this

Hi, I have been experimenting for a while with tryCandidate() method of the pre-RA mischeduler. I have by chance found some parameters that give quite good results on benchmarks on SystemZ (on average 1% improvement, some improvements of several percent and very little regressions). Basically, I add a "latency heuristic boost" just above processor resources checking:

Hi all, I have two sets: dig<-c("DAVID ADAMS","PIERS AKERMAN","SHERYLE BAGWELL","JULIAN BAJKOWSKI","CANDIDA BAKER") import<-c("by DAVID ADAMS","piersAKERMAN","SHERYLE BagWEL","JULIAN BAJKOWSKI with ","Cand BAKER","smith green")     I want to get the following result from

I am using the AICmodavg package and using R version 2.15.1. I need help with code that is instead being read as text. Below is a subset of code... I actually have 12 models, but I am trying to get this to work for 2 below right now. Everything 'appears' to work through the line starting with Modnames. After that the code starting with aictab and beyond is recognized as text and not

Hi R-helpers, I have a character object called dd that has 32 elements each of which is a model formula contained within quotation marks. Here's what it looks like: > dd [1] "lm(y ~ 1,data=Cement)" "lm(y ~ X,data=Cement)" "lm(y ~ X1,data=Cement)" [4] "lm(y ~ X2,data=Cement)" "lm(y ~

I am using the "predict" function on a support vector machine (svm) object, and I don't understand why I can't predict on a dataset with more observations than the training dataset. I think this problem is a generic "predict" problem, but I'm not sure. The original svm was fit on 50 observations.

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",