similar to: Expected behavior from: all(c(NA, NA, NA) < NA, na.rm = TRUE)?

------- 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

(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(

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() returns an NA (with a warning) if the count is greater than 2^31. For example: > xx <- runif(3e9) > sum(xx < 0.9) [1] NA Warning message: In sum(xx

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 align with the behavior of length() and sum()) Cheers, H. On 01/27/2018 03:06 AM, Martin Maechler wrote: >>>>>> Henrik Bengtsson <henrik.bengtsson at gmail.com>

>>>>> 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

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: In sum(x) : integer overflow - use sum(as.numeric(.)) > y <- matrixStats::sum2(x, mode = "double") > y [1] 2147483648 > str(y) num 2.15e+09 No coercion is taking place, so the

Hi all, Just a quick heads up that I made the plunge into F7 this week. R version 2.5.0 Patched (2007-06-05 r41831) compiles and passes make check-all. F7 is using: [marcs at Bellerophon ~]$ gcc --version gcc (GCC) 4.1.2 20070502 (Red Hat 4.1.2-12) Some quick F7 notes: 1. Do a clean install rather than an 'in place' upgrade from FC6 or a prior version. There are a lot of changes,

gives an error in R. In both S+3 and S+5, it "works" by returning NULL or logical(0), respectively. As a consequence, all(x == y) returns TRUE in Splus, when x <- y <- NULL but gives an error in R. Do we have a good reason *not* to return logical(0) ? Martin Maechler <maechler@stat.math.ethz.ch> http://stat.ethz.ch/~maechler/ Seminar fuer Statistik, ETH-Zentrum LEO

Hi, Please consider the following : x = c(1,3,NA,5) y = c(2,NA,4,1) min(x,y,na.rm=TRUE) # ok [1] 1 max(x,y,na.rm=TRUE) # ok [1] 5 sum(x,y,na.rm=TRUE) # ok [1] 16 pmin(x,y,na.rm=TRUE) # ok [1] 1 3 4 1 pmax(x,y,na.rm=TRUE) # ok [1] 2 3 4 5 psum(x,y,na.rm=TRUE) [1] 3 3 4 6 # expected result Error: could not find function "psum" # actual result

Hello, sum(data.frame(),na.rm=TRUE) still throws an Error, is this really the intended behavior? > sum(data.frame()) Error in FUN(X[[1L]], ...) : only defined on a data frame with all numeric or complex variables > sum(data.frame(),na.rm=TRUE) Error in FUN(X[[1L]], ...) : only defined on a data frame with all numeric or complex variables The context is # x is a data frame generated from

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. 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

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

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

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

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