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Dear R community, I have a question on how R manages memory allocation in .Fortran() calls under Windows. In brief, apparently, it is not possible to allocate large matrices inside a Fortran subroutine unless you pass them as arguments. If you do not act in this way RGUI crashes with a stack overflow error and acting on memory through vsize nsize ppsize and memory.limit does not help at all.

Hi the list, I am writing a function in which I need to affect a variable on a higher level. My fnction could be: ++++++++++++++++++ fooBis <- function(x){ nameObject <- deparse(substitute(x)) print(nameObject) assign(nameObject,4,envir=parent.frame()) } > fooBis(e) [1] "e" > e [1] 4 ----------------- (to simplify, this fnction can affect only the number

I?m wondering which is the most efficient (time, than memory usage) way to obtain a multivariate time series object from a data frame (the easiest data structure to get data from a database trough RODBC). I have a starting point using timeSeries or xts library (these libraries can handle time zones), below you can find code to test. Merging parallelization (cbind) is something I?m thinking at

...when i attempt to use smtp auth from a mail client, postfix says SASL plain authentication failed unable to lookup user record smtp authentication also fails if i use the usual command line method: # telnet localhost 25 Escape character is '^]'. 220 osx-106.example.com ESMTP Postfix EHLO foobie.example.com 250-osx-106.example.com 250-PIPELINING 250-SIZE 10485760 250-VRFY 250-ETRN 250-AUTH LOGIN PLAIN CRAM-MD5 250-STARTTLS 250-ENHANCEDSTATUSCODES 250-8BITMIME 250 DSN AUTH PLAIN blah blah blah 535 Error: authentication failed i've scoured months worth of postfix and dovecot list archiv...