On 13-06-22 2:34 PM, Radford Neal wrote:
I have released a new, faster, version of R, which I call pqR (for
"pretty quick" R), based on R-2.15.0. Among many other improvements,
pqR supports automatic use of multiple cores to perform numerical
computations in parallel with other numerical computa
Hi
I migrated from Linux to Mac, but I don't this has anything to do with
it, but I am not sure.
I am writing a small logger package, in which I have a file
aaa.R:
,
| .logData <- new.env()
| assign("loggingThreshold", 10, envir = .logData)
| assign("logToFile", FALSE, envir = .logData
Section 1.4 of Writing R Extensions is very clear about what not to do with
makefiles in the vignettes or inst/doc directory. It provides a BAD
EXAMPLE.
But it doesn't say (to me) what does work. So what does?
As I read the text, it seems that just removing the clean prerequisite from
the all ta
On 25/06/2013 16:52, Rong lI Li wrote:
Hi, all,
Recently, I met one issue when using socket between R & C++ to transmit R
object. Would you pls help give me some suggestions? Many thanks!
R-help was really the wrong list: see the posting guide. And multiple
posting is really discouraged.
B
On 25 June 2013 at 17:12, Prof Brian Ripley wrote:
| On 25/06/2013 16:52, Rong lI Li wrote:
| > I found actually, the saveRDS writes the R object with XDR format. I could
|
| It may do ... depending how you call it. You may prefer to serialize()
| to a raw vector whose size you can find, and tr
Should the F statistic be the same when using add1() on models created by lm
and glm(family=gaussian)?
They are in the single-degree-of-freedom case but not in the
multiple-degree-of-freedom case.
MASS:addterm shows the same discrepancy. It looks like the deviance
(==residual sum of squares) ge
Hi Hervé,
thank you for the link, I like the convolve2() function, it is
definitely a more user-friendly version of convolve().
I still believe that convolve() would be worth improving for the R stats
package, since it is pretty important in signal processing. I think it
would be great to ha
> stats:::add1.glm
function (object, scope, scale = 0, test = c("none", "Rao", "LRT",
"Chisq", "F"), x = NULL, k = 2, ...)
{
Fstat <- function(table, rdf) {
dev <- table$Deviance
df <- table$Df
diff <- pmax(0, (dev[1L] - dev)/df)
Fs <- (diff/df)/(dev/(rdf
Hi Michael,
On 06/25/2013 12:07 PM, Michael Moers wrote:
Hi Hervé,
thank you for the link, I like the convolve2() function, it is
definitely a more user-friendly version of convolve().
I still believe that convolve() would be worth improving for the R stats
package, since it is pretty importan
Hi Rainier,
On 06/25/2013 04:04 AM, Rainer M Krug wrote:
Hi
I migrated from Linux to Mac, but I don't this has anything to do with
it, but I am not sure.
I am writing a small logger package, in which I have a file
aaa.R:
,
| .logData <- new.env()
| assign("loggingThreshold", 10, envir
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