similar to: applying max elementwise to two vectors

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.

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, 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) >

I have two variables in a data frame, I want to generate two additional variables. For every observations (i.e. every row), I want the first new variable 'min' to carry the minimum of the two existing variables, and I want the second new variable 'max' to carry the maximum of the two existing variables. I then want to sort the data frame by min and max, and delete duplicated rows

Dear helpeRs, I seem to be a little bit confused on the result I am getting from the few codes below: > u=v=seq(0,1,length=30) > u [1] 0.00000000 0.03448276 0.06896552 0.10344828 0.13793103 0.17241379 [7] 0.20689655 0.24137931 0.27586207 0.31034483 0.34482759 0.37931034 [13] 0.41379310 0.44827586 0.48275862 0.51724138 0.55172414 0.58620690 [19] 0.62068966 0.65517241 0.68965517 0.72413793

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 =

I have two lists of equal lengths. Each one consists of vectors. Is there an elegant way to combine them elementwise? Elegant means: without loops. For instance, for > jja_list(1:3,4:7) > jjb_list(rep(0,4),(2,5)) I would like to get: > list(c(1:3,rep(0,4)),c(4:7,rep(2,5))). --- D.Trenkler --- ************************************************************************ *********

Hi How do I concatenate two lists element-by-element? Example: list.1 <- list(temperature=c("hot","cold") , size=c("big","medium")) list.2 <- list(temperature=c("lukewarm") , size=c("massive","tiny")) list.wanted <- list(temperature=c("hot","cold","lukewarm") ,

Dear All, Further to answers to sorting, can someone tell me how can I sort a list that contains duplicates (name) but keeping the duplicates together when sorting the values. e.g., a data frame with name (in duplicates), Mvalues(may be different for the duplicates) name M 1234 8 1234 8.3 4321 9 4321 8.1 If I sort by M, it will be 1234, 4321, 1234, 4321 but I want to keep the duplicates together,

All, I'm trying to obtain a one-liner to generate a certain sequence of alternatign numbers. Consider: > unlist(rep(list(c(1,2), c(3,4)), each = 6)) [1] 1 2 1 2 1 2 1 2 1 2 1 2 3 4 3 4 3 4 3 4 3 4 3 4 I'd like the result to be as above but continue until 38. Of course, I could hardcode this going up to c(37,38), but is there a more elegant way? Thanks! David

All, Simple question but I don't seem to be able to find the answer in the documentation: When using "plot" within a loop, is there any way to supply the argument to "main" dynamically, i.e., so that the title is Patient k below as the loop cycles through each value of k? plot(x,y, xlim=c(0,250), ylim=c(0,1000), xlab="gamma", ylab="r1",

Full_Name: Xiao Gang FAN Version: 2.4.0 OS: Windows XP Submission from: (NULL) (159.50.101.9) Dear All, This is not really a bug report, but rather a change wish to the Base R behaviour on some functions when applying them to character strings vectors/matrices. Actually in R, we can do thinks like, the most naturally way in this the world: > "a" < "b" [1] TRUE >

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

Has anyone got a function for smooth monotonic interpolation of a univariate function? I'm after something like the NAG function PCHIM which does monotonic Hermite interpolation. Alternatively, montononic cubic spline interpolation. Please reply directly. Rob Hyndman ___________________________________________________ Rob J Hyndman Associate Professor & Director of Consulting

All, Is there an efficient way to apply say "mean" or "median" to a dataframe according to say all combinations of two variables in the dataframe? Below is a simple example and the outline of a "manual" solution that will work but is not very efficient (could also generalize this to a function). Searched the archives and docs but didn't see anything close to

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

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

Dear all, Can anyone please shed some light onto how to do this? This will give me all "intensity" columsn in my data frame: intensityindeces <- grep("^Intensity",names(dataframe),value=TRUE) This will give me the maximum intensity for the first row: intensityone <- max(dataframe[1,intensityindeces]) What I'm now looking for is how to dfo this for the whole data

Greetings. For R gurus this may be a no brainer, but I could not find pointers to efficient computation of this beast in past help files. Background - I wish to implement a Cramer-von Mises type test statistic which involves double sums of max(X_i,Y_j) where X and Y are vectors of differing length. I am currently using ifelse pointwise in a vector, but have a nagging suspicion that there is a