search for: sfsappli

Dear All, I have a question of how to export S4 class specification to clusters/workers in parallel computing. The package I used is snowfall. The problem is reproducible as follows. Any hint is greatly appreciated. Edwin Sun === begin =========== library(snowfall) sfInit(parallel = TRUE, cpus = 2) setClass("catt", representation(aa = "numeric")) setClass("dogg",

Hi All, I have a question about R parallel computing by using snowfall. How can I set the seeds on parallel workers to get the same result as sequential mode? For example: > sfSapply(c(1,1),rnorm) [1] 1.823082 -2.222052 > rnorm(2) [1] -0.5179967 -1.0807196 How to get the identical result? Thanks. Libo Sun Graduate Student, Department of Statistics, Colorado State University Fort

Hi All, I'm wanting to convert a ragged list of values into a structured matrix for further analysis later on, i have a solution to this problem (below) but i'm dealing with datasets upto 1GB in size, (i have 24GB of memory so can load it) but it takes a LONG time to run the code on a large dataset. I was wondering if anyone had any tips or tricks that may make this run faster? Below is

Merry Xmas to all, I am writing a function and curiously this runs sometimes on one data set and fails on another and i cannot figure out why. Any help much appreciated. If i run the code below with data <- iris[ ,1:4] The code runs fine, but if i run on a large dataset i get the following error (showing data structures as matrix is large) > str(cluster.data) num [1:9985, 1:811] 0 0 0 0

Hi, I'm working in R 2.11.1 x64 on Windows x86_64-pc-mingw32. I'm experiencing a strange problem in R that I'm not even sure how to begin to fix. I've got a huge (forty-pages printed) simulation written in R that I'd like to run multiple times. When I open up R and run it on its own, it works fine. At the beginning of the program, there's a variable X that I set to 1,

Hi, if i have data in the following time series format: time, amount, state 1 2222 A 1 333 B 2 45 A 2 77 B where states could be n and time periods t is there a package in R that would calculate the transition probabilities in a markov chain. for each t except t=0 to generate A B A B perhaps the best structure might