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...directory) >dyn.load("deldirld.o") Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library "D:\Reza\476\tv.gonsrc.R\deldirld.o": LoadLibrary failure ************************************************************************** Reza S. Mahani e-mail: mahani at uiuc.edu Department of Economics phone(Office): (217) 333-4581 University of Illinois at Urbana-Champaign phone(Home): (217) 384-0987 330 comm. west, 1206 S. sixth st. FAX: (217) 244-6678 Champaig...

...ongly suspect that the BLAS function itself isn't what takes the bulk part of the time, but perhaps data transfer and other overhead associated with the calls (.C and .Call) are the main issues. Are there any ways to reach the performance level of native R code in this case? Thank you, Alireza Mahani -- View this message in context: http://r.789695.n4.nabble.com/Performance-of-C-and-Call-functions-vs-native-R-code-tp3665017p3665017.html Sent from the R devel mailing list archive at Nabble.com.

..."f" in C and calling it from R using ".C" interface. I know that I can use function pointers for my C implementation, but I imagine it's going to be nearly impossible to pass a function from R to C. Are there any exact or approximate solutions available? Thank you, Alireza Mahani -- View this message in context: http://r.789695.n4.nabble.com/Is-it-possible-to-pass-a-function-argument-from-R-to-compiled-code-in-C-tp3827563p3827563.html Sent from the R devel mailing list archive at Nabble.com.

...can be made to avoid crashing R by raising the stack limit: http://www.r-bloggers.com/using-openmp-ized-c-code-with-r/ However, trying this in my .C function doesn't help things. Any suggestions/tips on whether I can safely use OpenMP inside a .C function, and if yes how? Thank you, Alireza Mahani -- View this message in context: http://r.789695.n4.nabble.com/How-to-safely-using-OpenMP-pragma-inside-a-C-function-tp3777036p3777036.html Sent from the R devel mailing list archive at Nabble.com.

I would like to load a binary file into R using load(), and then assign a new name to it, regardless of the name it was saved under. Can you please provide a code sample? Thank you! -- View this message in context: http://r.789695.n4.nabble.com/Assigning-a-new-name-to-object-loaded-with-load-tp4638144.html Sent from the R help mailing list archive at Nabble.com.

I am developing an R package for internal use, and eventually for public release. My understanding is that there is no easy way to avoid copying function arguments in R (i.e. we don't have the concept of pointers in R), which makes me wary of freely creating chains of function calls since each function call implies data copy overhead. Is the above assessment fair? Are there any good write-ups

How can I abort running a script if I determine it's taking too long? Currently, I simply close the R window and re-open it. Thank you! -- View this message in context: http://www.nabble.com/Abort-run-tp23852410p23852410.html Sent from the R help mailing list archive at Nabble.com.

I am writing a wrapper function in C++ that calls a GPU kernel. My array type for the GPU kernel is float, so I would like my wrapper function to receive float arrays from R. I understand that I can use 'as.single' in R to copy a double-precision vector from R in single-precision format while using the '.C' interface, but is there any way to do something similar for

I'm trying to estimate a two-tier model with varying intercepts and slopes across 20 groups, with each group having about 50 observations and with no group predictor. I use the command lmer(y~x+(1+x | group)). But the result is a constant intercept (zero standard deviation, all 20 intercept values are the same). I'm puzzled; am I setting up my model wrong, or is the algorithm

I have a function myFunction(beta,x) where beta is a vector of coefficients and x is a data frame (think of it as a matrix). I want to optimize the function myFunction() by ONLY changing beta, i.e. x stays constant, with 4 constraints. I have the following code (with a separate source file for the function): rm(list=ls()) source('mySourceFile')

Further pursuing my curiosity to measure the efficiency of R/C++ interface, I conducted a simple matrix-vector multiplication test using .C and .Call functions in R. In each case, I measured the execution time in R, as well as inside the C++ function. Subtracting the two, I came up with a measure of overhead associated with each call. I assume that this overhead would be non-existent of the entire

I am developing a custom regression package, which accepts a formula object as way of setting up the model matrix and response variable from a data frame. For large data sets, I expect that going through R memory might be too slow, so I'm thinking about reading the data directly into C (e.g. from a database) and then parsing the formula inside of C (by calling an R function such as

I have a question for the R core development team: Are there any near-term plans to incorporate the ODBC API function SQLBulkOperations into the RODBC package? As you are probably well aware, the sqlSave() function uses a row-by-row insert (even in the 'fast' version) that imposes heavy DB transaction overheads as well as unnecessary network transmission overheads. Replacing the current