Luke,
I'm happy to help with this. Its great to see this get tackled (I've cc'ed
Kelli Ottoboni who helped flag this issue).
I can prepare a patch for the RNGkind related stuff and the doc update.
As for ???, what are your (and others') thoughts about the possibility of
a) a reproducibility API
Good day,
It is implemented by the CRAN package multicon. The function is named popsd.
But it does seem like something R should provide without creating a package
dependency.
--
Dario Strbenac
University of Sydney
Camperdown NSW 2050
Australia
___
I don't know if this will get much response from the R developers;
they might just recommend that you protect your mle() call in a try() or
tryCatch() to stop it from breaking your loop. Alternatively, you could
try mle2() function in the bbmle package, which started out long ago as
a slightly
This SO question may be of interest:
https://stackoverflow.com/questions/38589705/difference-between-rs-sum-and-armadillos-accu/
which points out that sum() isn't doing anything fancy *except* using
extended-precision registers when available. (Using Kahan's algorithm
does come at a computat
Hi all,
Several people have noticed that gregexpr is very slow for large subject
strings when perl=TRUE is specified.
-
https://stackoverflow.com/questions/31216299/r-faster-gregexpr-for-very-large-strings
-
http://r.789695.n4.nabble.com/strsplit-perl-TRUE-gregexpr-perl-TRUE-very-slow-for-long-str
Before the next release we really should to sort out the bias issue in
sample() reported by Ottoboni and Stark in
https://www.stat.berkeley.edu/~stark/Preprints/r-random-issues.pdf and
filed aa a bug report by Duncan Murdoch at
https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17494.
Here are
The algorithm does make a differece. You can use Kahan's summation
algorithm (https://en.wikipedia.org/wiki/Kahan_summation_algorithm) to
reduce the error compared to the naive summation algorithm. E.g., in R
code:
naiveSum <-
function(x) {
s <- 0.0
for(xi in x) s <- s + xi
s
}
kahanSum
(I didn't see anyone else answer this, so ...)
You can probably find the R code in src/main/ but I'm not sure. You are
talking about a very simple calculation, so it seems unlike that the
algorithm is the cause of the difference. I have done much more
complicated things and usually get machine
Hi, R developers.
when running mle inside a loop I found a nasty behavior. From time to
time, my model had a degenerate minimum and the loop just crashed. I
tracked it down to "vcov <- if (length(coef)) solve(oout$hessian)" line,
being the hessian singular.
Note that the minimum reached was goo
> As far as I can tell, the manual help page for ``sd``
>
> ?sd
>
> does not explicitly mention that the formula for the standard deviation is
> the so-called "Bessel-corrected" formula (divide by n-1 rather than n).
See Details, where it says
"Details:
Like 'var' this uses denominator n
I cannot file suggestions on bugzilla, so writing here.
As far as I can tell, the manual help page for ``sd``
?sd
does not explicitly mention that the formula for the standard deviation is
the so-called "Bessel-corrected" formula (divide by n-1 rather than n).
I suggest it should be stated near
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