similar to: Help with operation on list of matrices

Dear List, Let's say I have a list whose components are 2 matrices (as exemplified in the "mylist" object below). I'd like to create a list with components being 4 matrices based on an logical index vector. is there a way to simplify what I'm doing to obtain the results in "mylist2"? I'd like something that would work on an arbitrary number of elements in

I keep finding myself in a situation where I want to calculate a variable name and then use it on the left hand side of an assignment. For example iteration <- 1 varName <- paste("run",iteration,sep="") myList$parse(text=varName) <- aColumn I want to take some existing variable "aColumn" and use the name "varName" name for it and put it into a

Dear List, This is an embarrassing question, but I can seem to make this work…How do I change the font size on the xlab and on the numbers shown in the x-axis on the time series plot below. The arguments cex.lab and cex.axis do not seem to be 'passing' to the plot function. plot(ts(rnorm(100), start=2004, freq=12), ylab="RQI", xlab="My X lab",

Hello dear R-users, I am currently trying to fill some datasatructure (array, list, hash...) with matrices that are calculated by a function and do vary in size: mylist = list() for(i in 1:n) mylist[i] = function(...) # returns a matrix print(mylist[1]) # prints only the first element of the matrix How can I store and afterwards access the matrices that are calculated by my function?

Dear all, I think that my question is very simple but I failed to solve it. I have a list which elements are matrices like this: >mylist [[1]] [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 [[2]] [,1] [,2] [,3] [1,] 7 9 11 [2,] 8 10 12 I'd like to create a matrix M<-mylist[[1]]+mylist[[2]] [,1] [,2] [,3] [1,] 8 12 16 [2,] 10 14 18

David, Thank you for responding to my post. Please consider the following output (typeregional is a factor having two levels, "regional" vs. "general"): Call: glm(formula = events ~ type, family = poisson(link = log), data = data, offset = log(SS)) Deviance Residuals: Min 1Q Median 3Q Max -43.606 -17.295 -4.651 4.204 38.421 Coefficients:

> On Oct 22, 2017, at 3:56 PM, Sorkin, John <jsorkin at som.umaryland.edu> wrote: > > David, > Thank you for responding to my post. > > Please consider the following output (typeregional is a factor having two levels, "regional" vs. "general"): > Call: > glm(formula = events ~ type, family = poisson(link = log), data = data, > offset =

David, Again you have my thanks!. You are correct. What I want is not technically a contrast. What I want is the estimate for "regional" and its SE. I don't mind if I get these on the log scale; I can get the anti-log. Can you suggest how I can get the point estimate and its SE for "regional"? The predict function will give the point estimate, but not (to my knowledge)

Hi all, I was unable to find a solution to my problem in the archives, but this might be due to a lack knowledge on the correct terminology on my part. Please forgive me if this has been explained before and please forgive me my probably clumsy way of explaining things. This is what I want to do: I have a list made up of 6 lists containing 7 4x4 matrices each. My goal is to select a large

Hi All, I'm planning to submit my first package to R, and although I read all the documentation, I'm not very clear on the following 2 items, from which I'd appreciate your guidance: 1)I understand it is suggested to use the R dev version to build the package. Which one specifically should I use to build a package on a Mac OS? How about package dependencies, which version should I

> On Oct 22, 2017, at 5:01 PM, Sorkin, John <jsorkin at som.umaryland.edu> wrote: > > David, > Again you have my thanks!. > You are correct. What I want is not technically a contrast. What I want is the estimate for "regional" and its SE. There needs to be a reference value for the contrast. Contrasts are differences. I gave you the choice of two references

Hello I tried to define replacement functions for the class "mylist". When I test them in an active R session, they work -- however, when I put them into a package, they don't. Why and how to fix? make_my_list <- function( x, y ) { return(structure(list(x, y, class="mylist"))) } mylist <- make_my_list(1:4, letters[3:7]) mylist mylist[['x']] <- 4:6

Dear List, I'm trying to solve this simple optimization problem in R. The parameters are the exponents to the matrix mm. The constraints specify that each row of the parameter matrix should sum to 1 and their product to 0. I don't understand why the constraints are not satisfied at the solution. I must be misinterpreting how to specify the constrains somehow. library(alabama) ff <-

Dear List, The gbm package on Win 7 produces different results for the relative importance of input variables in R 32-bit relative to R 64-bit. Any idea why? Any idea which one is correct? Based on this example, it looks like the relative importance of 2 perfectly correlated predictors is "diluted" by half in 32-bit, whereas in 64-bit, one of these predictors gets all the importance

Hi All, I didn't have much success through my Google search in finding any active R-related projects to create a wrapper around TensorFlow in R. Anyone know if this is on the go? Thanks, Axel. [[alternative HTML version deleted]]

Hi All, I didn't have much success through my Google search in finding any active R-related projects to create a wrapper around TensorFlow in R. Anyone know if this is on the go? Thanks, Axel. [[alternative HTML version deleted]]

Dear R users, I know this issue came up in the list several times. I’m currently running R on 32-bit on Windows and due to memory limitation problems would like to move to a 64-bit environment. I’m exploring my options and would appreciate your expertise: 1) Windows 64-bit: Prof. Brian Ripley recently posted the experimental built of R for win 64-bit. I’ll appreciate any feedback on

Hi All, I'd like to build a package for the community that replicates the output produced by SAS "proc varclus". According to the SAS documentation, the first few steps are: 1. Find the first two principal components. 2. Perform an orthoblique rotation (quartimax rotation) on eigenvectors. 3. Assign each variable to the rotated component with which it has the higher squared

I can define a list containing NULL elements: > myList <- list("aaa",NULL,TRUE) > names(myList) <- c("first","second","third") > myList $first [1] "aaa" $second NULL $third [1] TRUE > length(myList) [1] 3 However, if I assign NULL to any of the list element then such element is deleted from the list: > myList$second <-

David, predict.glm and se.fit were exactly what I was looking for. Many thanks! John John David Sorkin M.D., Ph.D. Professor of Medicine Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 (Phone) 410-605-7119 (Fax)