similar to: IEEE 754 Style Arithmetic

Hi, I'm determined to get R compiling & running on a machine running AIX 4.2. I've seen previous emails in the archive about this topic. The main obstacle is getting dynamic loading to work, but it works for Tcl and hence is feasable. Questions: - is anybody _currently_ working with R on AIX? - why have previous fixes to the sources not been introduced into the released

Hi, I'm determined to get R compiling & running on a machine running AIX 4.2. I've seen previous emails in the archive about this topic. The main obstacle is getting dynamic loading to work, but it works for Tcl and hence is feasable. Questions: - is anybody _currently_ working with R on AIX? - why have previous fixes to the sources not been introduced into the released

Hi, I already found a conversation on the integration of a normal distribution and two suggested solutions (https://stat.ethz.ch/pipermail/r-help/2007-January/124008.html): 1) integrate(dnorm, 0,1, mean = 0, sd = 1.2) and 2) pnorm(1, mean = 0, sd = 1.2) - pnorm(0, mean = 0, sd = 1.2) where the pnorm-approach is supposed to be faster and with higher precision. I want to integrate a mixed

Dear all, I need to do some calculation where the code used are below. I get error message when I choose k to be large, say greater than 25. The error message is "Error in integrate(temp, lower = 0, upper = 1, k, x, rho, m) : the integral is probably divergent". Can anyone give some help on resolving this. Thanks. Hannah m <- 100 alpha <- 0.05 rho <- 0.1 F0

Hi, I would have thought that these two constructions would produce the same result but they do not. Resp <- rbinom(10, 1, 0.5) Stim <- rep(0:1, 5) mm <- model.matrix(~ Stim) Xb <- mm %*% c(0, 1) ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) pnorm(as.vector(Xb), lower.tail = Resp, log.p = TRUE) > ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) [1] -0.6931472 -1.8410216

LLVM does not support IEEE decimal-floating point. If by “fixed point arithmetic” you are asking about associating a scale factor with a variable/value, and doing the correct scaling for arbitrary arithmetic… LLVM doesn’t do that either. It’s a rare IR that even has the concept. The OpenVMS GEM compilers supported it (along with other special features for COBOL), but I’m not aware of any

Hi, Does LLVM support decimal precision numbers supported? Also does it have Fixed point arithmetic? S -- Suminda Sirinath Salpitikorala Dharmasena, B.Sc. Comp. & I.S. (Hon.) Lond., P.G.Dip. Ind. Maths. J'Pura, MIEEE, MACM, CEO Sakrīō! ▣ *Address*: 6G • 1st Lane • Pagoda Road • Nugegoda 10250 • Sri Lanka. ▣ *Mobile* : +94-(0)711007945 ▣ *Tele*: +94-(0)11-5 864614 / 5 875614 / 2 825908 ▣

Also Q numbers format can be added for added precision. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20130910/a78890c2/attachment.html>

> This will come in handy if you do not have a floating point unit. Also for > speed in some cases. > > To be generic as possible it might be good to have this. The goal isn't really maximum generality, but support for languages that people care about. Currently that's mostly C and C++, with a smattering of features for some others. But features almost never get added

These features can find use in embedded micro controllers and situation where you do not want rounding errors. x86 and ppc sound like Intel and Power PC specific. Of course once introduced some one must maintain it. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20130910/8cff2269/attachment.html>

On 9 September 2013 20:21, Suminda Dharmasena <sirinath at sakrio.com> wrote: > These features can find use in embedded micro controllers and situation > where you do not want rounding errors. Not until someone comes up with a language specifying them (or at least a highly suspect variant of C specifying them) they can't. Tim.

Many thanks for getting back. This will come in handy if you do not have a floating point unit. Also for speed in some cases. To be generic as possible it might be good to have this. BTW, in the doc I was reading there was not mention about Quad size numbers, decimal numbers and extended precision numbers. http://llvm.org/docs/LangRef.html#type-system -------------- next part -------------- An

First, I love R and am grateful to be using this free and extremely high quality software. Recently I have been comparing two algorithms and naturally I programmed in R first. It is so slow that I can almost feel its pain. So I decided to do a comparison with Java. To draw 500,0000 truncated normal, Java program takes 2 second and R takes 72 seconds. Not a computer science major, I find it hard

Hi everyone, I am new to R, but it's really great and helped me a lot! But now I have 2 questions. It would be great, if someone can help me: 1. I want to integrate a normal distribution, given a median and sd. The integrate function works great BUT the first argument has to be a function so I do integrate(dnorm,0,1) and it works with standard m. and sd. But I have the m and sd given.

Hi, I want to generate random samples from truncated normal say Normal(0,1)Indicator((0,1),(2,4)). It has more than one intervals. In the library msm, it seems to me that the 'lower' and 'upper' arguments can only be a number. I tried rtnorm(1,mean=0,sd=1, lower=c(0,2),upper=c(1,4)) and it didn't work. Can you tell me how I can do truncated normal at more than one intervals?

I found the following strange behavior using qnorm() and pnorm(): > x<-8.21;x-qnorm(pnorm(x)) [1] 0.0004638484 > x<-8.22;x-qnorm(pnorm(x)) [1] 0.01046385 > x<-8.23;x-qnorm(pnorm(x)) [1] 0.02046385 > x<-8.24;x-qnorm(pnorm(x)) [1] 0.03046385 > x<-8.25;x-qnorm(pnorm(x)) [1] 0.04046385 > x<-8.26;x-qnorm(pnorm(x)) [1] 0.05046385 > x<-8.27;x-qnorm(pnorm(x))

I would like to generate pseudo-random numbers between two numbers using R, up to a given distribution, for instance, rnorm. That is something like rnorm(HowMany,Min,Max,mean,sd) over rnorm(HowMany,mean,sd). I am wondering if dnorm(runif(HowMany, Min, Max), mean, sd) is good. Any idea? Thanks. -james

Hi all, I have the following two function f1 and f2. f1 <- function(lambda,z,p1){ lambda*(p1*exp(-3*z-9/2)+(0.2-p1)*exp(4*z-8))-(1-lambda)*0.8} f2 <- function(p1,cl, cu){ 0.8*(pnorm(cl)+(1-pnorm(cu)))/(0.8*(pnorm(cl)+(1-pnorm(cu)))+p1*(pnorm(cl+3)+(1-pnorm(cu+3)))+(0.2-p1)*(pnorm(cl-4)+(1-pnorm(cu-4))))}-0.05 First fix p1 to be 0.15. (i) choose a lambda value, say lamda=0.6, (ii)

Hi all. I may be wrong, (and often am), but in trying to determine how to calculate the erf function, the documentation for 'pnorm' states: ## if you want the so-called 'error function' erf <- function(x) 2 * pnorm(x * sqrt(2)) - 1 ## and the so-called 'complementary error function' erfc <- function(x) 2 * pnorm(x * sqrt(2), lower=FALSE) Should, instead, it read:

Dear all, Can anyone take a look at my program below? There are two functions: f1 (lambda,z,p1) and f2(p1,cl, cu). I fixed p1=0.15 for both functions. For any fixed value of lambda (between 0.01 and 0.99), I solve f1(p1=0.15, lambda=lambda, z)=0 for the corresponding cl and cu values. Then I plug the calculated cl and cu back into the function f2. Eventually, I want to find the lambda value