Hi,
I've been running some simulations for a while and the performance of R has been great. However, I've recently changed the code to perform a sort of chi-square goodness-of-fit test. To get the observed values for each cell I've been using table() - specifically I've been using cut2 from Hmisc to divide up the range into a specified number of cells and then using table to count how many observations appear in each cell.
obs <- table(cut2(z.trun, cuts=breaks))
Having done this I've found that the code takes much longer to run - up to 10x as long. Is there a more effecient way of doing this? Anyone have any thoughts?
-- SC
Simon Cullen Room 3030 Dept. Of Economics Trinity College Dublin
Ph. (608)3477 Email [EMAIL PROTECTED]
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