search for: stranda

Hi All, I'm trying to take a numerical vector and produce a new vector of the same length where each element in the first is placed into a category given by a 'breaks-like' vector. The values in the result should equal the lower bounds of each category as defined in the breaks vector. I suspect that a vectorized solution is pretty simple, but I can't seem to figure it

Hi All, I'm trying to specify the formula for a glm based upon the names in the data.frame. I always discard the first two variables in the frame and the third will always be the only response variable. The problem appears because I would like to specify the rest of the variables of the data.frame as independent variables in the formula. I can't think of a way to do this cleanly and

Hi all, I am interested in calculating and displaying the distributions of pairwise comparisons between DNA sequences in populations. The comparisons are the number of nucleotide sites that differ between the two sequences (mismatches). My sequences are stored in a vector of strings. There is an additional vector of the same length that provides the indices to the DNA sequences. Finally, I

Hi All, I'm trying to come up with a clear and concise (and fast?) solution to the following problem. I would like to take a vector 'v' and enumerate all of the ways in which it can be broken into n sets of length 2 (if the length of the vector is odd, and an additional set of length 1). An element of 'v' can only appear in one set. Order within sets is not important.

I've been trying to learn about dynamically loading subroutines in R. Ultimately I would like to use this approach to implement some simulations. For the moment though, I've run into a problem compiling c++ code and loading it into R. The 'C/C++' and 'R'code below works fine when compiled and linked with gcc, but gives an error when the library is compiled and linked with

Hi all, This is as much as statistical/estimation question as an R-specific one, but here goes. I am trying to use logistic regression to predict suitability of habitats for certain plant species. The response variable is a binary one that indicates whether a particular species is found at a site on the landscape. The independent variables represent physical characteristics of the landscape