similar to: Generalised rbind/cbind

I'm attempting to generalise a function that reads individual list components, in this case they are matrices, and converts them into 3 dimensional array. I can input each matrix individually, but want to do it for about 1,000 of them ... This works array2 <- abind(list1[[1]],list1[[2]],list1[[3]],along=3) This doesn't array2 <- abind(list1[[1:3]],along=3) This doesn't either

(resent as hotmail really cannot format plaintext, but I've just read Tony Plate's message that what I'd like to do might not be possible) > > library(abind) ## array binding I've looked into using abind() but it seems I might not understand it properly. I can build my 2 table array and insert a row into each table using: x <- array(0,c(1,3,2)) x[,,1]

I'm trying to massage some data from Matlab into R. The matlab file has a "struct array" which when imported into R using the R.matlab package, becomes an R list with 3+ dimensions, the first of which corresponds to the structure fields, with corresponding row names, and the second and third+ dimensions correspond to the dimensions of the original struct array (as matlab

Hi. Can anyone suggest a simple way to obtain in R a list of vector coordinates of the following form? The code below is Mathematica. In[5]:= Flatten[Table[{i,j,k},{i,3},{j,4},{k,5}], 2] Out[5]= {{1,1,1},{1,1,2},{1,1,3},{1,1,4},{1,1,5},{1,2,1},{1,2,2},{1,2,3},{1 ,2,4},{1,2, 5},{1,3,1},{1,3,2},{1,3,3},{1,3,4},{1,3,5},{1,4,1},{1,4,2},{1,4,3}, {1,4,

Dear R users, I'm hoping that more experienced users will be able to assist me in examining the model fit of a mixed generalised linear model. The example using the data 'bacteria' within the MASS package will hopefully illustrate what I would like to acheive; library(MASS) library(nlme) attach(bacteria) # y being output and the trt - treatment group being an explanatory variable.

Readers, I have been reading 'the r book' by Crawley and think that the generalised additive model is appropriate for this problem. The package 'gam' was installed using the command (as root) install.package("gam") ... library(gam) > library(gam) Loading required package: splines Loading required package: akima > library(mgcv) This is mgcv 1.3-25 Attaching

Dear R Help Community, I have a question and an answer (based on reading this forum and online research), but I though I should share both since probably there's a much better way to go about my solution. My question is specifically about how to best visualise multiple response contingency tables. What I mean by 'multiple response' is that the total number of responses per row of a

Dear R users, I have used the following model: M1 <- gls(Nblad ~ Concentration+Season + Concentration:Season, data=DDD, weights=varIdent(form=~ 1 | Season*Concentration)) to assess the effect of Concentration and Season on nitrogen uptake by leaves (Nblad). I accounted for the difference in variance across the factor levels by using the varIdent function. Then I wanted to perform multiple

Hi everyone I've been playing with do.call() but I'm having problems understanding it. I have a list of "n" elements, each one of which is "d" dimensional [actually an n-by-n-by ... by-n array]. Neither n nor d is known in advance. I want to bind the elements together in a higher-dimensional array. Toy example follows with d=n=3. f <-

Hi I have two arbitrarily dimensioned arrays, "a" and "b", with length(dim(a))==length(dim(b)). I want to form a sort of "corner-to-corner" version of abind(), or a multidimensional version of blockdiag(). In the case of matrices, the function is easy to write and if a=matrix(1,3,4) and b=matrix(2,2,2), then adiag(a,b) would return: [,1] [,2] [,3] [,4] [,5]

Dear R users I am analysing data from a group of twins and their siblings. The measures that we are interested in are all correlated within families, with the correlations being stronger between twins than between non-twin siblings. The measures are all calculated from survey answers and by definition have limited ranges (e.g. -5 to +5), though within the range they are approximately normally

Hi, I have recently been attempting to find the LD50 from two predicted fits (For male and females) in a Generalised linear model which models the effect of both sex + logdose (and sex*logdose interaction) on proportion survival (formula = y ~ ldose * sex, family = "binomial", data = dat (y is the survival data)). I can obtain the LD50 for females using the dose.p() command in the MASS

Dear R-users, we are using library(snow) for computation on a linux cluster with RMPI. We have a problem with clusterEvalQ: after launching clusterEvalQ it seems loading the required library on each node but if we type a function belonging to the loaded package R doesn't find it. > library(snow) # making cluster with 3 nodes > cl <- makeCluster(3, type = "MPI") Loading

### I got bit again by the same bugs I wrote about a year ago. ### The bugs are related to matrices and arrays of lists. ### 1. There is a clear inconsistency in how R handles two ### functionally equivalent statements. ### array() is able to take a list and create a matrix. ### matrix() is unable to create that matrix. > vector("list", 2) [[1]] NULL [[2]] NULL >

Hi everybody, I have trouble in installing packages from source code by following Section 5.1 in manual R-admin.pdf . I am using R 2.1.0 and Win NT. Following the Windows toolset section in the manual, I download the tool set package from: http://www.murdoch-sutherland.com/Rtools/tools.zip and unzip under C:\tools I also downloaded Perl (Windows Port) and installed it.

Hi, I'm new to R. Apologies if this is a simple query, I've searched the mailing lists and docs but can't find a solution to my problem. I'm trying to make some packages available on our intranet. During development the 'intranet' is a webserver running on localhost. * When I call "install.packages" I get a mesage about not being able to access 'index

I am trying to combine two arrays with different dimensions into one. For example The first one is 1 2 3 4 5 6 The second one is 7 8 9 10 The resulted one would be like , , 1 1 2 3 4 5 6 , , 2 7 8 9 10 I used abind to do this, but failed. Could somebody please let me know how to do this in R? Thanks so many. Suyan

Hi, I would like to add rows to arbitrary tables within a 3dimensional array. I can directly add data to an existing row of a table: > x <- array(0,c(1,3,2))> x[,,1] <- c(1,2,3) And I can even add a row to the table and assign to another object. > y <- rbind(x[,,1], c(4,5,6)) and 'y' is what I want it to be:> y?? ? [,1] [,2] [,3][1,] ? ?1 ? ?2 ? 3[2,] ? ?4 ? ?5 ? 6 but

Must packages in the Depends field of the DESCRIPTION file have NAMESPACES? I haven't seen this explicitly indicated anywhere. I am writing a small package and find that when I add the abind package to the list of the Depends field, I get an error in R CMD check of the build. * checking package name space information ... OK * checking package dependencies ... ERROR Packages required but not

Hello, I would like some help with my Generalised Linear Model in R-Studio I am a little confused about what family to use and for my data My outcome variable (response) is categories 0,1,2,3 but my data i dont have any individuals that have fallen into the top group "3" What i have read about Generalised Models is that Biomial data is only two option not the 4 that i have. What