search for: data_funct

I wanted to create a list of functions whose output differs depending the value of a variable when the function was created. Generally this did not work. Each function was exactly the same, as in the simple example below: get_data_function <- function(v) { function() { print(v) } } data_functions <- sapply(1:10,function(v) get_data_function(v)) (data_functions[[1]])() # prints 10! However, if I insert a statement in get_data_function to print argument v, then I get the different functions that I wanted: get_data_fu...

...") grep -e 'read.table; *.SSC indicates that the read.table() function is called in ReadIBD.SSC on lines seven and twelve, and that the error is occuring with the second read.table() where the file '_Data\\TempFile' is being read (see copy of ReadIBD.data.SSC below). ReadIBD.data_function(file) { ### Funtion to read the IBD probability data from GENEHUNTER ### This data was generated from using "Dump IBD" command in GENEHUNTER ### File = ibd.out file from genehunter temp_read.table(file, skip=1, col.names=c("pos","pedid", "pair",...

Hi All: I'm new to R and have a few questions about getting R to run efficiently with large datasets. I'm running R on Windows XP with 1Gb ram (so about 600mb-700mb after the usual windows overhead). I have a dataset that has 4 million observations and about 20 variables. I want to run probit regressions on this data, but can't do this with more than about 500,000 observations before