similar to: sum(data.frame(),na.rm=TRUE) still throws an Error

Hi all, I get two different results when using sum() and the switch na.rm. The result is correct when na.rm=FALSE. Linux Redhat 7.3, R version 1.6.1. I've had no luck searching the mail archives, so I was hoping somebody could explain/check this one for me. I will need to apply the function to missing data, simple as it is. Code: x<-matrix(runif(20,0,5)%/%1,4,5) # random matrix

Hi: I remember a post several days ago by Jon Baron, concerning the behavior of sum() when one sets na.rm=TRUE: the result will be a zero sum for a vector of all NA's, as here, for the second row: > ss<- data.frame(x=c(1,NA,3,4),y=c(2,NA,4,NA)) > ss x y 1 1 2 2 NA NA 3 3 4 4 4 NA > apply(ss,1,sum,na.rm=TRUE) 1 2 3 4 3 0 7 4 I am rather alarmed by that zero, because

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system

Dear R-developers, =20 according to the "what's new"-section in version R 2.7.0, there has been = a change in the working of co[rv] and so also in sd and var. =20 I am afraid, that the use of function sd with option "na.rm=3DT" has not = been changed appropriately. So the following problem exists with missing = data: =20 > sessionInfo() R version 2.7.0 (2008-04-22)=20

The weighted.mean() function replaces NA values with 0.0 when the user specifies na.rm=TRUE: x <- c(101, 102, NA) mean(x, na.rm=TRUE) # 101.5, correct weighted.mean(x, na.rm=TRUE) # 67.66667, wrong weighted.mean(x, w=c(1,1,1), na.rm=TRUE) # 67.66667, wrong weighted.mean(x, w=c(1,1,1)/3, na.rm=TRUE) # 67.66667, wrong The weights are

Hello! Is it possible to set na.rm=TRUE in a global way? I'am constantly forgeting on this when performing analyses. I agree that one should be carefull with this when developing some code, but not necesarilly so in data analysis. Lep pozdrav / With regards, Gregor Gorjanc ---------------------------------------------------------------------- University of Ljubljana PhD student

POS=sum(x[-1][x[-1]>0],na.rm=TRUE) is this the correct syntax? -- View this message in context: http://r.789695.n4.nabble.com/na-rm-TRUE-tp2299596p2299596.html Sent from the R help mailing list archive at Nabble.com.

Hi all! I need to do something really simple using do.call. If I want to call the mean function inside do.call, how do I apply the condition na.rm=TRUE? So, I use do.call(mean, list(x)) where x is my data. This works fine if there are no NAs. Thanks, John [[alternative HTML version deleted]]

Hi all, Came across this curious behavior in: R version 2.5.0 Patched (2007-06-05 r41831) A simplified example is: > all(c(NA, NA, NA) > NA, na.rm = TRUE) [1] TRUE Is this expected by definition? If one reduces this to individual comparisons, such as : > NA > NA [1] NA > all(NA > NA) [1] NA > all(NA > NA, na.rm = TRUE) [1] TRUE the initial comparison on the 3

Hi. I'm comparing output from rollapply.zoo, as produced by two versions of R and package zoo. I'm illustrating with an example from a R-help posting 'Zoo - bug ???' dated 2010-07-13. My question is not about the first version, or the questions raised in that posting, because the behaviour is as documented. I'm puzzled as to why na.rm no longer is passed to mean, i.e. why

All, I've been using aggregate() to compute means and standard deviations at time/treatment combinations for a longitudinal dataset, using na.rm = TRUE for missing data. This was working fine before, but now when I re-run some old code it isn't. I've backtracked my steps and can't seem to find out why it was working before but not now. In any event, below is a reproducible

------- Start of forwarded message ------- Date: Tue, 13 Nov 2007 21:44:57 +0100 To: Steve Mongin <sjm at ccbr.umn.edu> Cc: cran at r-project.org Subject: Re: range( <dates>, na.rm = TRUE ) In-Reply-To: <200711062044.OAA14064 at minnow.ccbr.umn.edu> Reply-To: Kurt.Hornik at wu-wien.ac.at From: Kurt Hornik <Kurt.Hornik at wu-wien.ac.at> X-AntiVirus: checked by AntiVir

>>>>> Herv? Pag?s <hpages at fredhutch.org> >>>>> on Fri, 2 Jun 2017 04:05:15 -0700 writes: > Hi, I have a long numeric vector 'xx' and I want to use > sum() to count the number of elements that satisfy some > criteria like non-zero values or values lower than a > certain threshold etc... > The problem is: sum()

I'm observing that base::sum(x, na.rm=FALSE) for typeof(x) == "double" is much more time consuming when there are missing values versus when there are not. I'm observing this on both Window and Linux, but it's quite surprising to me. Currently, my main suspect is settings in on how R was built. The second suspect is my brain. I hope that someone can clarify the below

I second this feature request (it's understandable that this and possibly other parts of the code was left behind / forgotten after the introduction of long vector). I think mean() avoids full copies, so in the meanwhile, you can work around this limitation using: countTRUE <- function(x, na.rm = FALSE) { nx <- length(x) if (nx < .Machine$integer.max) return(sum(x, na.rm =

>>>>> Henrik Bengtsson <henrik.bengtsson at gmail.com> >>>>> on Thu, 25 Jan 2018 09:30:42 -0800 writes: > Just following up on this old thread since matrixStats 0.53.0 is now > out, which supports this use case: >> x <- rep(TRUE, times = 2^31) >> y <- sum(x) >> y > [1] NA > Warning message:

(Drats! Jitterbug is playing tricks with the PR# again. Attempting to refile so that we can kill PR#10509) Peter Dalgaard wrote: > Kurt.Hornik at wu-wien.ac.at wrote: > =20 >> ------- Start of forwarded message ------- >> Date: Tue, 13 Nov 2007 21:44:57 +0100 >> To: Steve Mongin <sjm at ccbr.umn.edu> >> Cc: cran at r-project.org >> Subject: Re: range(

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Tue, 6 Jun 2017 09:45:44 +0200 writes: >>>>> Herv? Pag?s <hpages at fredhutch.org> >>>>> on Fri, 2 Jun 2017 04:05:15 -0700 writes: >> Hi, I have a long numeric vector 'xx' and I want to use >> sum() to count the number of

I have now committed a version "fulfilling" your wish, partly at least, to R-devel . In the new approx(*, na.rm=FALSE) cases, the result of how NA's are treated does depend on the 4 different extrapolation rules {1, 2, 1:2, 2:1} The main reason was that I kept the low level code in C to do +- what it did before which automatically was using 'rule' to determine these

>>>>> Herv? Pag?s <hpages at fredhutch.org> >>>>> on Tue, 30 Jan 2018 13:30:18 -0800 writes: > Hi Martin, Henrik, > Thanks for the follow up. > @Martin: I vote for 2) without *any* hesitation :-) > (and uniformity could be restored at some point in the > future by having prod(), rowSums(), colSums(), and others >