search for: kkelley

Hello Everyone, I've been told that the memory allocation in R and S-Plus is different, with R being better at doing simulations for whatever reason(s). I was wondering if anyone could enlighten me on the differences in the memory usage/allocation (preferably in layman's terms!). The reason I ask this is because of a simulation I am trying to run. In it, I need to use the pt( )

This seems like it should have an obvious answer, but I haven't seen a clear word one way or the other in the man pages or other documentation that I have read - is smbmount's behavior in any way governed by the smb.conf file? The reason I ask is one of the other sysadmins here has been trying to figure out ways to improve smbfs performance, and he came across the speed.txt file in

Hello all. I was wondering if anyone had insight into how I might generate a large number of data sets/vectors, where each of the data sets/vectors have a different name? For example, suppose I wanted to generate N data sets/vectors, each with a different name such as: Random.Data.1 <- rnorm(10, 0, 1) Random.Data.2 <- rnorm(10, 0, 1) Random.Data.3 <- rnorm(10, 0, 1) . . . . .

Hello all. I was wondering if the logLike.nls() and logLike.nlme() functions are still being used. Neither function seems to be available in the most recent release of R (1.9.1). The following is contained in the help file for logLik(): "classes which already have methods for this function include: 'glm', 'lm', 'nls' and 'gls', 'lme' and others in

Hello all. I'm doing a large scale simulation study and every so often I get an error that stops the simulation. I would like to ignore the errors and identify the particular iterations where they occurred. I have tried: options(error = expression(NULL)) which I thought would ignore the error, but the simulation is still stopped when an error occurs. I do not think try() is a good idea

Hi everyone. I'm working with nlme and I have a question regarding nlme fits that fail because of singularity issues. Specifically, there a way to return an nlme object when the estimation process runs into a singular matrix? For example, can the results up to the point of an error such as "Error in solve.default(pdMatrix(a, fact = TRUE)) : system is computationally singular" or

Hello all. I'm wresting with a very weird smbfs quirk. I realize smbfs works independently of the Samba package (aside from smbmount's work), so please let me know if I should be asking this question in another forum. We store email directories on a Win2K Server (SP2), with two email servers (Red Hat 7.1, kernel 2.4.9-34) accessing the share. One specific directory has a curious

Hello all. I was wondering if there is any way to adjust the denominator degrees of freedom in lme(). It seems to me that there is only one method that can be used. As has been pointed out previously on the list, the denominator degrees of freedom given by lme() do not match those given by SAS Proc Mixed or HLM5. Proc Mixed, for example, offers five different options for computing the