similar to: qunif() behavior with Inf arguments (PR#8958)

Hi everyone, I use the boot package within the MBESS package to automate much of the hard part for folks interested in performing a (simple) mediation model. The function mediation() works well, except for a (probably) unrealistic artificial data set. When I apply the bootstrap I sometimes get: Error in t.star[r, ] <- res[[r]] which is (I think) due to Inf and -Inf and NaN values produced for

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

Full_Name: G?ran Brostr?m Version: 2.3.1 OS: Linux, ubuntu Submission from: (NULL) (85.11.40.53) > dweibull(0, 0.5, 1) [1] NaN Warning message: NaNs produced in: dweibull(x, shape, scale, log) should give Inf (and no Warning). Compare with > dgamma(0, 0.5, 1) [1] Inf This happens when 'shape' < 1.

I stumbled across this and I am wondering if this is unexpected behavior or if I am missing something. > pnorm(-1.0e+307, log.p=TRUE) [1] -Inf > pnorm(-1.0e+308, log.p=TRUE) [1] NaN Warning message: In pnorm(q, mean, sd, lower.tail, log.p) : NaNs produced > pnorm(-1.0e+309, log.p=TRUE) [1] -Inf I don't know C and am not that skilled with R, so it would be hard for me to look into

NIST maintains a repository of Statistical Reference Datasets at http://www.itl.nist.gov/div898/strd/. I have been working through the datasets to compare R's results to their references with the hope that if all works well, this could become a validation package. All the linear regression datasets give results with some degree of accuracy except one. The NIST model includes 11 parameters,

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>

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 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

I am attempting to fit discrete data (daily counts of arrivals of recreational vessels at locks on a river) using the fit.dist package. Some distributions return values of NaN and Inf for certain situations, an example with Inf values is shown below. # of vessels: 1 2 3 4 5 6 7 8 9 10 11 # of days with # of vessels: 35 20 10 5 6

I am not certain how nlme works so I followed an example from the web ( http://www.menne-biomed.de/gastempt/gastempt1.html). I was able to successfully reproduce the example. However, when I modified my the example to use my data and with my formula, I get a set of errors having to do with the log() function. I get 10 of them (all exactly the same) and there are 10 levels in my factor variable.

>>>>> Gabriel Becker >>>>> on Tue, 5 Mar 2019 22:01:37 -0800 writes: > On Tue, Mar 5, 2019 at 9:54 PM Richard White <w at rwhite.no> wrote: >> Hi Gabriel, >> >> The point is that it *visually* displays as NA, but is.na() still >> responds as FALSE. >> >> When I (and I am sure many people)

Full_Name: Patrick Burns Version: 1.8.1 OS: Windows 2000 Submission from: (NULL) (81.129.3.151) The command: eigen(matrix(Inf, 2, 2)) causes version 1.8.1 to hang in both Windows 2000 and SuSe 8.2. (Hang defined as apparently needing to kill the process in order to get a prompt back.) This is similar to bug #4366 where the same command used NaN instead of Inf.

>>>>> peter dalgaard >>>>> on Sun, 8 Dec 2019 12:11:50 +0100 writes: > Yes, that looks like a bug and an easily fixable one too. agreed. > However, I spy another issue: Why do we check the > !R_FINITE(x) && mu == x before checking for sd < 0 ? The > difference is whether we > return ML_NAN; or ML_ERR_return_NAN;

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, The specification for the llvm.minnum/llvm.maxnum intrinsics is too unclear right now to usefully optimize. There are two problems. First the expected behavior for signaling NaNs needs to be clarified. Second, whether the returned value is expected to be canonicalized (as if by llvm.canonicalize). Currently according to the LangRef: Follows the IEEE-754 semantics for minNum, which also

Good question, I cannot speak for R's developers but I would like to provide some information on the problem. Here are the first few lines of the dnorm function located at src\nmath\dnorm.c: ``` double dnorm4(double x, double mu, double sigma, int give_log) { #ifdef IEEE_754 if (ISNAN(x) || ISNAN(mu) || ISNAN(sigma)) return x + mu + sigma; #endif if(!R_FINITE(sigma)) return R_D__0;

Hi, > James, is that a correct assessment? Yes, it is also my belief that the only way ARMv7 NEON differs from IEEE754 is lack of denormal support. James > On 11 Feb 2016, at 10:53, Renato Golin <renato.golin at linaro.org> wrote: > > Hal, > > I had a read on the ARM ARM about VFP and SIMD FP semantics and my > analysis is that NEON's only problem is the

Hello, I am new with R, and I'm trying to fit a linear model, I did the following and obtein this result, can anybody help? Thanks, > logdftodos7925vi <- log(dftodos7925vi) > logALTURA7925<- log(dftodos7925$ALTURA7917) > logtodos7925.lm <- lm (logALTURA7925~., data= logdftodos7925vi) Error en lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : NA/NaN/Inf en

Hi If I have a <- Inf + 1i then Re(a) is Inf, and Im(a) is 1, as expected. But if b <- 1 + Inf * 1i, then Im(b) = Inf , as expected, but Re(b) = NaN, which I didn't expect. Why this asymmetry? How to define an object with Re(b)=1, Im(b)=Inf? -- Robin Hankin Uncertainty Analyst Southampton Oceanography Centre European Way, Southampton SO14 3ZH, UK tel 023-8059-7743