similar to: Element-by-element multiplication operator?

Hi All I am having 2 very long character strings (550chars) and I want to put them as expressions together with c(). The problem is that I also get these double-quotes, as seen below in 'fct'. How can I remove these double-quotes? I tried as.name() but it did not work (because of size?). These are creating trouble with subsequent programs, which I tested with strings that for some

Dear R buddies, This weekend I became interested in solving Google Code Jam problems using R. I guess R may work very well in this kind of contests but the input of file has been a problem for me. Take this case for example (http://code.google.com/codejam/contest/dashboard?c=agdjb2RlamFtchALEghjb250ZXN0cxjRzBQM), the files are usually of the form: A(number of lines for group 1) a11 a12 a13 a21

I am fitting models to the responses to a questionnaire that has seven yes/no questions (Item). For each combination of Subject and Item, the variable Response is coded as 0 or 1. I want to include random effects for both Subject and Item. While I understand that the datasets are fairly small, and there are a lot of invariant subjects, I do not understand something that is happening

Dear all: I'm trying to fit the optimal Box-Cox transformation related to nls (see the code below) for the demand of money data in Green (3th Edition) but in the last step R gives the next error message. Error en `[.data.frame`(eval(object$data), , as.character(formula(object)[[2]])[2]) : undefined columns selected. ?Any idea to solve the problem? Thanks in advance,

Dear Colleagues, I have a dataframe with variables: [1] "ID" "category" "a11" "a12" "a13" "a21" [7] "a22" "a23" "a31" "a32" "b11" "b12" [13] "b13" "b21"

Hi, Is there any package that I can use to simulate the Gaussian Mixture Model , which is a mixture modeling method that is widely used in statistical learning theory. I know there is a mclust, however, I think it is a little bit different from my problem. Thanks very much.. regards. -------------------------- Peng Jiang ?? Ph.D. Candidate Antai College of Economics &

Dear helpers, I wrote a code which estimates a multi-equation model with generalized least squares (GLS). I can use GLS because I know the covariance matrix of the residuals a priori. However, it is a bit slow and I wonder if anybody would be able to point out a way to make it faster (it is part of a bigger code and needs to run several times). Any suggestion would be greatly appreciated. Carlo

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

r-devel list, I have recently written an R package that solves a linear least squares problem, and computes the multivariate normal density function. The bulk of the code is written in C, with interfacing code to the BLAS and Lapack libraries. The motivation here is speed. I ran into a problem computing the determinant of a symmetric matrix in packed storage. Apparently, there are no explicit

Hi there, I would like to find a more efficient way of permuting the rows and columns of a symmetrical matrix that represents ecological or actual distances between objects in space. The permutation is of the type used in a Mantel test. Specifically, the permutation has to accomplish something like this: Original matrix addresses: a11 a12 a13 a21 a22 a23 a31 a32 a33 Example

Dear all, suppose I have a vector with elements as: Vec <- c(2,3,4,5,6) Now I want to have all possible combination of length 3 using those elements and without any repetition. Like, I want to have 1 possibility like 2-3-4 but not 3-2-4. Can somebody guide me how to achieve that in R? Thanks for your help.

I was working with the rmetrics portfolioBacktesting function and dug into the code to try to find why my formula with 113 items, i.e. A1 thru A113, was being truncated and I only get 85 items, not 113. Is it due to a string length limitation in R or is it a bug in the strsplit or gsub functions, or in my string? I'd very much appreciate any suggestions ============Input script:

> > If one compares the random effect estimates, in fact, one sees that > > they are in the correct proportion, with the expected signs. They are > > just approximately eight orders of magnitude too small. Is this a bug? > > BLUPs are essentially shrinkage estimates, where shrinkage is > determined with magnitude of variance. Lower variance more > shrinkage towards

I am fitting models to the responses to a questionnaire that has seven yes/no questions (Item). For each combination of Subject and Item, the variable Response is coded as 0 or 1. I want to include random effects for both Subject and Item. While I understand that the datasets are fairly small, and there are a lot of invariant subjects, I do not understand something that is happening here, and in

We have recently digitized a set of points from some scanned engineering drawings (in the form of PDFs). The digitization resulted in x,y page coordinates for each point. The scans were not aligned perfectly so there is a small rotation, and furthermore each projection (e.g. the yz-plane) on the drawing has a different offset from the page origin to the projection origin. From the dimensions

Good morning! Please, could you help me with the problem? I have a matrix *144x73.* An example of a matrix: [,1] [,2] [,3] [,4] [,5] [1,] 277.4 276.24 275.62 276.55 278.05 [2,] 277.4 276.24 275.55 276.42 277.72 [3,] 277.4 276.24 275.50 276.22 277.39 [4,] 277.4 276.24 275.42 276.02 277.02 [5,] 277.4 276.22 275.37 275.82 276.64 And I want to *compare*its cells

I want to change the type to factor of all variables in a data frame whose names match a certain pattern. So here I am trying to change the type to factor of all variables whose name begins with?namestub?in the dataframe?df. attach(df)sapply(grep(glob2rx("namestub*"),names(df)),as.factor) But this doesn't work since >levels(df$namestub1)NULL

I realize this should be simple, but even after reading over the several help pages several times, I still cannot decide between the myriad "apply" functions to address it. I simply want to apply a function to all the rows (or columns) of the same index from two (or more) identically sized arrays (or data frames). For example: > a=matrix(1:50,nrow=10) >

Hi, I have a function of the second grade, with 2 parameters: y~A^2 + A + B^2 + B The response y is a measurement for the precision of the analytical method, where A en B are method parameters. As its neccesary to keep the precision of the analytical methad as good as possible, its usefull to optimize A en B to keep y as low as possible. But how can I do this with R? I have searched the

A long formula which is converted using as.character, looses its last part: ``diagonal = 1e-12)'' Shorter formula is ok though. Best, H??vard ************ Browse[2]> formula.str y ~ -1 + b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8 + b9 + b10 + b11 + b12 + b13 + b14 + b15 + b16 + b17 + b18 + b19 + b20 + b21 + b22 + b23 + b24 + b25 + b26 + b27 + b28 + b29 + b30 + b31 + b32 +