similar to: Question about converting from square roots to decimals and back

Hello! I stumbled upon something odd that took a while to track down, and I wanted to run it by here to see if I should submit a bug report. For randomly generated numbers (from a variety of distributions) rounding them to specifically 2 digits and then multiplying them by 100 produces strange results on about 8% of cases. The problematic numbers display as I would have expected, but do not

Try this: 0.7-0.3==0.4 (We get FALSE) 0.7-0.3<0.4 (We get TRUE) but 0.8-0.3==0.5 (TRUE) 0.8-0.3<0.5 (FALSE) Funny, he? There is a way around: round(0.7-0.3,1)==0.4 (TRUE) Obviously there is a problem with some combinations of decimal subtractions, that - we have the feeling - shouldt be solved. Best regards Sven & Wolfgang -- View this message in context:

Try this: 0.7-0.3==0.4 (We get FALSE) 0.7-0.3<0.4 (We get TRUE) but 0.8-0.3==0.5 (TRUE) 0.8-0.3<0.5 (FALSE) Funny, he? There is a way around: round(0.7-0.3,1)==0.4 (TRUE) Obviously there is a problem with some combinations of decimal subtractions, that - we have the feeling - shouldt be solved. Best regards Sven & Wolfgang -- View this message in context:

Hi R, I have certain checkings, which gives FALSE, but actually it is true. Why does this happen? Note that the equations that I am checking below are not even the case of recurring decimals... > 1.4^2 == 1.96 [1] FALSE > 1.2^3==1.728 [1] FALSE Thanks in advance, Shubha Shubha Karanth | Amba Research Ph +91 80 3980 8031 | Mob +91 94 4886 4510 Bangalore * Colombo *

Hi, Why the qr() produces a negative Q compared with Gram-Schmidt? (note example below, except Q[2,3]) Here is an example, I calculate the Q by Gram-Schmidt process and compare the output with qr.Q() a <- c(1,0,1) b <- c(1,0,0) c <- c(2,1,0) x <- matrix(c(a,b,c),3,3) ########################## # Gram-Schmidt ########################## A <- matrix(a,3,1) q1 <-

Dear All, I have a problem understanding the difference between the outcome of a fisher exact test and a chi-square test (with simulated p.value). For some sample data (see below), fisher reports p=.02337. The normal chi-square test complains about "approximation may be incorrect", because there is a column with cells with very small values. I therefore tried the chi-square with

Hi, there, I cannot get accurate value for calculation. for example: ld<-sqrt(1*0.05*0.95*0.05*0.95) 0.05*0.95-ld=-6.938894e-18 0.05*0.95-ld==0 is False. I met this problem in my program, how can I handle it. Thanks. xj.

Hello R experts, I'd like to studentize a matrix (tmp1) by column using apply() function and skip some specific values such as zeros in the example below to tmp2 but not tmp3. I used the script below and only can get a matrix tmp3. Could you please help me to studentize the matrix (tmp1) without changing the zeros and generate a new matrix tmp2? Thanks, Joshua tmp1 [,1] [,2] [,3] [,4]

Full_Name: jan hattendorf Version: 2.9.0 OS: XP Submission from: (NULL) (213.3.108.185) I get an incorrect result for (41/10-1/10)%%1 [1] 1 The error did not occur with other numbers than 41 (1, 11, 21, 31, 51, ...) test <- rep(NA, 1000) for(i in 1:1000){ test[i] <- i/10-1/10 } test[test%%1==0]

Hi, I just observed a strange behavior in R. The rnorm function does not give me the numbers with a given length. I think it is somehow related to the internal representation of double-type numbers but I am not sure if this is supposed to happen. Below is a reproducible example ``` ## Create a list, we will only take the forth value, which is 0.6 nList <- seq(0,1,0.2) n <- nList[4] n # [1]

Hi, I'm trying to calculate some functions loop, unfortunately my data are decimal numbers that not allow me to get an accurate estimate. I do not want to use neither "round "nor "signif" but I would prefer to have all the information available, (the function loop is generic so you should adapt to all data, not just those in particular). The approximation error is

Hi, I'm having trouble with the "which" or the "seq" function, I'm not sure. Here's an example : > lat=seq(1,2,by=0.1) > lat [1] 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 > which(lat==1) [1] 1 > which(lat==1.1) [1] 2 > which(lat==1.2) [1] 3 > which(lat==1.3) [1] 4 > which(lat==1.4) [1] 5 > which(lat==1.5) [1] 6 >

Dear colleagues Please could someone kindly explain the following inconsistencies I've discovered when performing logical calculations in R: 8.8 - 7.8 > 1 > TRUE 8.3 - 7.3 > 1 > TRUE Thank you, Emma Jane [[alternative HTML version deleted]]

Hi all, In checking my R codes, I encountered the following problem. Is there a way to fix this? I tried to specify options(digits=). I did not fix the problem. Thanks so much for your help! Hanna > cdf(pmass)[2,2]==pcum[2,2][1] FALSE> cdf(pmass)[2,2][1] 0.9999758> pcum[2,2][1] 0.9999758 [[alternative HTML version deleted]]

Hi I searched in the list and only found questions without answers e.g. http://finzi.psych.upenn.edu/R/Rhelp02a/archive/19955.html : Is there a way to get the same results with lme as with aov with Error()? Can anybody reproduce the following results with lme: id<-c(1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,1,1,1,2,2,2,3,3,3,4,4,4,5,5,5)

> length(sample(25000, 25000*(1-.55))) [1] 11249 > 25000*(1-.55) [1] 11250 > length(sample(25000, 11250)) [1] 11250 > length(sample(25000, 25000*.45)) [1] 11250 So the question is, why do I get 11249 out of the first command and not 11250? I can't figure this one out. Thanks Cory [[alternative HTML version deleted]]

Hi, I recently spent quite a bit of time trouble shooting a function that I had written only to discover that the problem I was having was with the comparison operator. I assumed that the following would return TRUE: > testMean <- 82.8 + 0.1 > testMean [1] 82.9 > testMean == 82.9 [1] FALSE Apparently this has to do with deciml places. Look: > newTest <- 82.0 > newTest [1]

Hi, I'm using the '%%' operator in some code, and am running into the following erroneous outcome: > 1.2 %% 0.2 [1] 0.2 Unless I'm very mistaken, the result should be 0 (indeed, 12 %% 2 does result in 0). Furthermore: > 1.20000000000000001 %% 0.2 [1] 0.2 > (1.2+1e17) %% .2 [1] 0 Warning message: probable complete loss of accuracy in modulus (Warning

I am trying to multiply a 3D array of 4x4x4 by the 4 3D arrays of a 4D array with dimensions 4x4x4x4 (the last dimension being the one that I want to split by). (4x4x4 array) > hiaAry , , a1 i1 i2 i3 i4 h1 9.5936098 6.001040 0.08772 0.3138600 h2 1.2003500 1.454570 2.79248 0.0000000 h3 0.1346500 0.201220 0.39256 0.5464000 h4 0.0109000 0.012270 0.16417 0.2766900 ,

Hello, When I am writing in sqldf or RSQLite I lose the decimals in my matrix. The only way I can get decimals is by multiplying by 1.00000, etc. I have tried manipulating the options, but it is only effective once I multiply by 1.0000. I appreciate any suggestions! Thanks! Example: z <- sqldf ("select ST, SUM(AGEP*PWGTP)*1.000000000/SUM(PWGTP)*1.00000000000000 as wgtage from ss09