[R] Lm gives different results depending on x-bit architecture

Dear all, I have encountered problem when developing application. My linear regression does give different results depending on architecture. Following example describes my problem perfectly. xxx <- data.frame(a=c(0.2,0.2,0.2,0.2,0.2),b=c(7,8,9,10,11)) lm(a~b,xxx) summary(lm(a~b,xxx)

Re: [R] ddply from plyr package - any alternatives?

No, it's not much faster. I'd say it's faster about 10-15% in my case. I dont want neither plyr or data.table package because our software on the server does not support R version over 2.10 and both of them have dependency for R >= 2.12. Also I do not want to use old archives because I did not ha

Re: [R] ddply from plyr package - any alternatives?

Thank you all for suggestions, they were great and informative. I will surely use data.tables in future when our server will be upgraded for now this is solution that I used. This solution performs exactly same task and produces exact same results at ddply. s <- split(past, paste(past$"CNTRY_N

Re: [R] ddply from plyr package - any alternatives?

Thank you for suggestions, apparently data.table is much quicker than ddply and it's fantastic to use. I forgot to mention in my topic I'm looking for alternative in R 2.10 version as on my platform our server runs older version of software which only support R up to version of R-2.10 (upgrade is

[R] ddply from plyr package - any alternatives?

Hello everyone, I was asked to repost this again, sorry for any inconvenience. I'm looking replacement for ddply function from plyr package. Function allows to apply function by category stored in any column/columns. Regular loops or lapplys slow down greatly because my unique combination count