similar to: pt inaccurate when x is close to 0 (PR#9945)

Hello, I have been playing around with the statistical distributions in R, and overall I think the accuracy is very good. However, it seems that for the Student's t distribution, the CDF loses accuracy when evaluated at values close to zero. For instance, I did the following in R ---------------------------------- df<-seq(1,100,by=1)

While I agree that the reported results from Mathematica have only 10-13 correct digits, that does not mean that pt() in R is any better for these calculations. For instance the following three calculations are mathematically equivalent, but pt() disagrees at the 13th figure in R v2.6.2 pt(1e-4,13) pf(1e-8,1,13)/2+0.5 pbeta(1/(1+13/1e-8),.5,6.5)/2+0.5 Using 1/(1+n/x^2) and reversing the

Here's a contribution from Ian Smith that got bounced from the list. -------- Original Message -------- Subject: Re: [Rd] pt inaccurate when x is close to 0 (PR#9945) Date: Thu, 11 Oct 2007 06:02:43 -0400 From: iandjmsmith at aol.com To: murdoch at stats.uwo.ca Duncan, I tried sending the rest of this to R-devel but it was rejected as spam, hence the personal e-mail. R calculates the pt

Dear R users, I?m trying to optimize simultaneously two binomials inequalities (used in acceptance sampling) which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

I would like to include a Mathematica notebook and cdf file (both are ASCII files) in the \inst\doc directory as supporting documentation. These files are not large, about 340K each one. When I check using R CMD check --as-cran ... I get the following warning: ...................... * checking data for ASCII and uncompressed saves ... OK WARNING 'qpdf' is needed for checks on size

On Sat, Dec 17, 2016 at 1:35 PM, Davide Italiano <davide at freebsd.org> wrote: [...] > I don't have an infrastructure to measure the runtime performance > benefits/regression of clang, but I have for `game7`. > I wasn't able to notice any fundamental speedup (at least, not > something that justifies a 2x build-time). > Just to provide numbers (using Sean's

On Dec 17, 2016 7:41 PM, "Sean Silva" <chisophugis at gmail.com> wrote: On Sat, Dec 17, 2016 at 6:32 PM, Davide Italiano via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On Sat, Dec 17, 2016 at 1:35 PM, Davide Italiano <davide at freebsd.org> > wrote: > [...] > > > I don't have an infrastructure to measure the runtime performance > >

Full_Name: Version: 2.7.1 (2008-06-23) OS: windows vista Submission from: (NULL) (216.82.144.137) Hello, I have been working with various probability distributions in R, and it seems the gamma distribution is inaccurate for some inputs. For example, qgamma(1e-100, 5e-101, lower.tail=FALSE) gives: 1.0. However, it seems this is incorrect; I think the correct answer should be

Dear R users, I?m trying to optimize simultaneously two binomials inequalities used to acceptance sampling, which are nonlinear solution, so there is no simple direct solution. The 'n' represents the sample size and the 'c' an acceptance number or maximum number of defects (nonconforming) in sample size. The objective is to obtain the smallest value of 'n' (sample size)

Hello all, In the course of trying to implement the CDF of an InverseGammaDistribution, I have run across the need for an igamma() function. Several others have needed this function but the answers I have found so far are not totally clear to me. I'm writing for three reasons: 1) to present a small error in the docs 2) to clarify the approach we are expected to take 3) to request,for the

Dear R users, I?m trying to optimize simultaneously two binomials inequalities used to acceptance sampling, which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

Hi People, I have just started building my own RPMS on both Fedora and CentOS and generally things have gone well. Currently I am trying to create RPMS for some commercial software that we have purchased. Step 1 was install the software using its JAVA Based installer ensuring that all files were installed into a particular directory in /usr/local. Step 2 was create a tar file of the

Hi, this is not an R-help post, but I found this extract below that was written by a leading mathematician back in 1999 when he was talking about statistics and computing. I found it interesting to share and I ask your opinion do you think this still holds today or things have changed? Thanks. ?...we would also like to mention that in our opinion Mathematica provides an excellent and indeed

What are some effective ways to leverage the strengths of R and Mathematica for the analysis of a single data set? More specifically, are there any functions that can assist with any of the following? 1. Calling an R function from Mathematica. 2. Calling a Mathematica function from R. 3. Using XML or another reliable data format to pass vectors, matrices, and/or lists from one environment to

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

Hello all, I would like to plot the emperical CDF, normal CDF and pareto CDF in the same graph and I amusing the following codes. "z" is a vector and I just need the part when z between 1.6 and 3. plot(ecdf(z), do.points=FALSE, verticals=TRUE, xlim=c(1.6,3),ylim=c(1-sum(z>1.6)/length(z), 1)) x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4373,-0.2398), col="red") y

I have some programs which were writen in mathematica or c language, but I donot know how to use these software. So I want to run them in R. Can I do it ? How to run "mathematica" or "c" programs in R? Jian Zhang [[alternative HTML version deleted]]

Hi R-users,   I have this code below and I understand the error message but do not know how to correct it.  My question is how do I get rid of “with absolute error < 7.5e-06” attach to value of cdf so that I can carry out the calculation.   integrand <- function(z) { alp  <- 2.0165   rho  <- 0.868   # simplified expressions   a      <- alp-0.5   c1     <-

Hi all, I am an R newbie trying to do some calculations I do in Mathematica in R on a GNU/Linux system. The main thing I am interested in doing is taking a 0.999 quantile on a data set in a file who's data is normally distributed, say foo.csv. e.g in Mathematica if I have something like this : a=Import["foo.csv"] b=Transpose[a][[1]] Quantile[b,0.999] In R I can load all the data

Hello! I have a problem with integrate() in my function nctspa(). Integrate produces an error message "evaluation of function gave a result of wrong length". I don't know what that means. Could anyone suggest me what is wrong with my function? These are the examples of function calls that work OK: nctspa(a=1:10,n=5) nctspa(a=1:10, n=5, mu=2, theta=3, renorm=0) This does not work: