similar to: Inconsistency in treating NaN-results?

As a side note, Splus makes sin(x) NA, with a warning, for abs(x)>1.6*2^48 (about 4.51e+14) because more than half the digits are incorrect in sin(x) for such x. E.g., in R we get: > options(digits=16) > library(Rmpfr) > sin(4.6e14) [1] -0.792253849684354 > sin(mpfr(4.6e14, precBits=500)) 1 'mpfr' number of precision 500 bits [1]

R and the S language that it is based on has evolved as much as it has been designed, so there are often inconsistencies due similar functionality evolving from different paths. In some cases these inconsistencies are resolved, but generally only once someone notices and care enough to do something about it. In some other cases the inconsistencies are left for historical reasons and for back

Joris, the point is that 'z' is NOT used as a predictor in the model. Therefore it should not affect predictions. Also, I find it suspicious that the error only occurs when the response variable conitains missings and 'z' is unique (I have tested several other cases to confirm this). -Mark Op vr 16 mrt. 2018 om 13:03 schreef Joris Meys <jorismeys at gmail.com>: >

Dear R-developers, In the 'lm' documentation, the '-' operator is only specified to be used with -1 (to remove the intercept from the model). However, the documentation also refers to the 'formula' help file, which indicates that it is possible to subtract any term. Indeed, the following works with no problems (the period '.' stands for 'all terms except the

hi, everybody, please help me with this question: If I want to do iteration for 1000 times, however, for the 500th iteration, there is NaN appears. Then the iteration will stop. If I don't want the stop and want the all the 1000 iterations be done. What shall I do? suppose I have x[1:1000] and z[1:1000],I want to do some calculation for all x[1] to x[1000]. z=rep(0,1000) for (i in 1:1000){

Hello, I notice in main/arithmetic.c, that NA and NaN are encoded differently(since every numeric NA comes from R_NaReal which is defined via ValueOfNA) . What is the benefit of treating these two differently? Why can't NA be a synonym for NaN? Thank you Saptarshi (R-2.9)

On Fri, Mar 31, 2017 at 10:14 PM, Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote: > From ?NA > > Numerical computations using ?NA? will normally result in ?NA?: a > possible exception is where ?NaN? is also involved, in which case > either might result. > > and ?NaN > > Computations involving ?NaN? will return ?NaN? or perhaps ?NA?: >

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

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 What does NaN mean? I recently did a correlation on a batch of data for some reason it didn't like one column cor(sleep,use="complete.obs") BodyWt BrainWt SlowSleep ParaSleep TotalSleep BodyWt 1.00000000 0.95584875 -0.3936373 -0.07488845 -0.3428373 BrainWt 0.95584875 1.00000000 -0.3867947 -0.07427740 -0.3370815 SlowSleep -0.39363729

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

Dear R developers, (Apologies about previous incomplete e-mail, I fat-fingered a keyboard shortcut)?? I recently upgraded to 3.2.3 and am getting mystifying errors with my in-development code (available at https://github.com/gertvv/gemtc/tree/feature/regression). Every few hundred LPs that I solve using the rcdd package will result in a SEGFAULT in the garbage collector (address 0x10, cause

Hi all.. I'm very new R, and i'm analyzing microarray data using Bioconductor.. Recently i was given microarray data to analyze. The problem is whenever i run MAS5 presence calls algorithm, it throws an error saying NA/NaN/Inf in foreign function. How do i remove such NA/NaN/Inf's ?? I tried na.omit(dataframe) but stil problem exists. dimension of matrix (data) is 35556 7. >

Hi! In a current project, I am fitting loess models to subsets of data in order to use the loess predicitons for normalization (similar to what is done in many microarray analyses). While working on this I ran into a problem when I tried to predict from the loess models and the data contained NAs or NaNs. I tracked down the problem to the fact that predict.loess will not return a value at all

I'm having trouble grokking complex NaN's. This first set examples using complex(re=NaN,im=NaN) give what I expect > Re(complex(re=NaN, im=NaN)) [1] NaN > Im(complex(re=NaN, im=NaN)) [1] NaN > Arg(complex(re=NaN, im=NaN)) [1] NaN > Mod(complex(re=NaN, im=NaN)) [1] NaN > abs(complex(re=NaN, im=NaN)) [1] NaN and so do the following > Re(complex(re=1,

Hi All, I have some data where I am doing fairly simple calculations, nothing more than adding, subtracting, multiplying and dividing. I’m running into a problem when I divide one variable by another and when they’re both 0 I get NaN. I realize that if you divide a non-zero by 0 then you get Inf, which is, of course, correct. But in my case I never get Inf, just NaN because of the structure

Dear all, I have a datafile where I run haplo.GLM analyses using several variables (a matrix). However, when I include a certain binary variable (0,1) I get this message Error: NA/NaN/Inf in foreign function call (arg 4) I don't get an error when I include another binary variable, again with only 0,1. Both variables don't have missing values, they only have 0 and 1. Why do I get an

In R 3.3.3, I observe the following on Ubuntu 16.04 (when building from source as well as for the sudo apt r-base build): > x <- c(NA, NaN) > mean(x) [1] NA > mean(rev(x)) [1] NaN > rowMeans(matrix(x, nrow = 1, ncol = 2)) [1] NA > rowMeans(matrix(rev(x), nrow = 1, ncol = 2)) [1] NaN > .rowMeans(x, m = 1, n = 2) [1] NA > .rowMeans(rev(x), m = 1, n = 2) [1] NaN >

In R, 0 ^ NaN yields Inf. I would have expected NaN or perhaps 0. Is this behaviour intended? >sessionInfo() R version 2.8.0 (2008-10-20) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils