similar to: highlighting constants

Greetings. I somehow had the impression that an infinite number, as obtained by dividing by zero, for instance, would be flagged as both missing ("NA") and not a number ("NaN"). It appears that I was wrong on both counts, although the is.finite function correctly returns FALSE in such a case. Please see the appended for some details. I guess that the bottom line is that R

If pi were stored and computed to infinite precision then yes we would expect tan(pi/2) to be NaN, but computers in general and R specifically don't store to infinite precision (some packages allow arbitrary (but still finite) precision) and irrational numbers cannot be stored exactly. So you take the value of the built in variable pi, which is close to the theoretical value, but not exactly

Hi All, I think there may be some possible confusion about what allowsInf would be reporting (or maybe its just me :) ) if we did this. Consider a class "myclass", S3, for starters, with setMethod("allowsInf", "myclass", function(obj) FALSE) Then, what would myclassthing <- structure(1.5, class = "mything") myclassthing[1] <- Inf do. Assumely it

So I tried adding Infinity support for all cases. And it is (as could be expected) more complicated than I thought. It is easy to add Inf support for the test. The problems start with conf.int=TRUE. Currently confidence intervals are computed via `uniroot()` and, in the case of infinities, we are computationally looking for roots over infinite interval which results in an error. I suspect this

>>>>> Martin Maechler >>>>> on Thu, 12 Dec 2019 17:20:47 +0100 writes: >>>>> Karolis Koncevi?ius >>>>> on Mon, 9 Dec 2019 23:43:36 +0200 writes: >> So I tried adding Infinity support for all cases. And it >> is (as could be expected) more complicated than I >> thought. > "Of course

The current situation is as follows. AIX: * I still need f77 for linking. Using ld with the suggested flags gives a binary with `exec format error'. The problem seems to be with an unreferenced __start. * The floating point (finite|isnan) stuff is strange, but under control, I think. Plain cc works, gcc has a problem and seems to need having prototypes turned off for IEEE fp.

Hi, I've spotted a possible memory leakage/violation in the latest R v2.1.1 patched and R v2.2.0dev on Windows XP Pro SP2 Eng. I first caught it deep down in a nested svd algorithm when subtracting a double 'c' from a integer vector 'a' where both had finite values but when assigning 'a <- a - c' would report NaNs whereas (a-c) alone would not. Different runs

Vince Carey found this (thank you!). Since the fix to the problem is not entirely obvious, I post this to R-devel as RFC: help(dist) says: >> Missing values are allowed, and are excluded from all computations >> involving the rows within which they occur. If some columns are >> excluded in calculating a Euclidean, Manhattan or Canberra >> distance, the sum is

>>>>> Karolis Koncevi?ius >>>>> on Mon, 9 Dec 2019 23:43:36 +0200 writes: > So I tried adding Infinity support for all cases. > And it is (as could be expected) more complicated than I thought. "Of course !" Thank you, Karolis, in any case! > It is easy to add Inf support for the test. The problems start with conf.int=TRUE.

Hi, OK, if you try to explicitly make them generic, you are told that they are implicitly already generic: > setGeneric("is.finite", function(from, ...) standardGeneric("is.finite")) Error in setGeneric("is.finite", function(from, ...) standardGeneric("is.finite")) : "is.finite" is a primitive function; methods can be defined, but the

Hi, I want to recode all Inf and NaN values to NA, but I;m surprised to see the result of the following code. Could anybody enlighten me about this? > df <- data.frame(a=c(NA, NaN, Inf, 1:3)) > df[is.infinite(df) | is.nan(df)] <- NA > df a 1 NA 2 NaN 3 Inf 4 1 5 2 6 3 > Thanks! Cheers!! Albert-Jan

Hi, I want to recode all Inf and NaN values to NA, but I;m surprised to see the result of the following code. Could anybody enlighten me about this? > df <- data.frame(a=c(NA, NaN, Inf, 1:3)) > df[is.infinite(df) | is.nan(df)] <- NA > df a 1 NA 2 NaN 3 Inf 4 1 5 2 6 3 > Thanks! Cheers!! Albert-Jan

Hi Micheal, On Mon, Oct 29, 2012 at 4:34 PM, Michael Ilseman <milseman at apple.com> wrote: > I > Flags > --- > no NaNs (N) > - ignore the existence of NaNs when convenient > no Infs (I) > - ignore the existence of Infs when convenient > no signed zeros (S) > - ignore the existence of negative zero when convenient > Does this mean ignore the possibility

Hello, I get the following prompt when tring to compute rlm: > x<-rlm(core.e, na.action=na.omit) >Error in qr(x) : NA/NaN/Inf in foreign function call (arg 1) I checked with is.finite and is.infinite but in both cases i get FALSE and my missing values are substituted by NA. what does this error prompt mean and how do I solve it? thanks in advance, cheers Martin -- Martin

Full_Name: Elizabeth Purdom Version: 1.9.1 OS: Windows Submission from: (NULL) (171.64.102.192) hist() fails if encounters 'Inf' value, rather than giving warning and removing. Other graphics, like plot(), don't have this problem. It's actually rather confusing if you are taking the log of data real valued data with a few non-positive numbers. hist() works fine in this situation

Reid Spencer wrote: > On Thu, 2007-03-22 at 15:50 -0700, leo han wrote: > >> Hello, I have a question about the constant folding for fdiv instructions. >> For the instruction "fdiv double 0.0, 0.0", the folded result is inf. I >> think this should be nan. Can anyone tell me why it is not nan? >> > > I think the specification says that it is

Jeff Cohen wrote: > Reid Spencer wrote: >> On Thu, 2007-03-22 at 15:50 -0700, leo han wrote: >> >>> Hello, I have a question about the constant folding for fdiv instructions. >>> For the instruction "fdiv double 0.0, 0.0", the folded result is inf. I >>> think this should be nan. Can anyone tell me why it is not nan? >>>

On Sun, 2010-01-31 at 13:28 +1100, Lang Hames wrote: > Hi Sebastian, > > It boils down to this: The previous heuristic solver could return > infinite cost solutions in some rare cases (despite finite-cost > solutions existing). The new solver is still heuristic, but it should > always return a finite cost solution if one exists. It does this by > avoiding early reduction of

Under windows, R supports IEEE floating point arithmetic, but doesn't allow conversion of Inf and NaN from character to numeric. R> is.nan(NaN) [1] TRUE R> as.numeric(as.character(NaN)) [1] NA Warning message: NAs introduced by coercion R> is.infinite(Inf) [1] TRUE R> as.numeric(as.character(Inf)) [1] NA Warning message: NAs introduced by coercion whereas under Linux R>

Dear R-users, i have to integrate the following function `fun1` <- function (a, l1, l2) { exp(log(l1) * (a - 1) - l2 * lgamma(a)) } but if l1 is large, i get the "non-finite function value" error, so my idea is to rescale with exp(-l1) `fun2` <- function (a, l1, l2) { exp(log(l1) * (a - 1) - l2 * lgamma(a) - l1) } but it seems this doesn't solve the problem, when