similar to: pgamma - inadequate algorithm design and poor coding (PR#8528)

On 23/02/05 I suggested that given R had included TOMS 708 to correct for t= he=20 poor performance of pbeta, TOMS 654 should be included to fix all the pgamm= a=20 problems. I was slightly surprised to find Morten's code had been included= =20 instead 2 days later. I noticed but did not worry that the reference to me = had=20 been removed.=20 The derivation of the asymptotic expansion for

Full_Name: Morten Welinder Version: 2 OS: Solaris/space/gcc2.95.2 Submission from: (NULL) (65.213.85.217) I changed src/nmath/standalone/test.c to read: --------------------------------------------------------------------------------- #define MATHLIB_STANDALONE 1 #include <Rmath.h> #include <stdio.h> int main() { double x; for (x = 99990; x <= 100009; x++) printf

In the current R-devel sources, the `pgamma' function gives a warning when the `shape' argument is passed as a vector of length > 1. That is, > pgamma(3, 1) [1] 0.950213 > pgamma(3, c(1, 2)) [1] 0.9502129 0.8008517 Warning message: the condition has length > 1 and only the first element will be used in: if (shape <= 0) stop("shape must be strictly positive")

I have DHCP and TFTP on a Solaris machine, pxelinux.0 loads, but it can't load the configuration file. The tftp server on Solaris tries to send the file, but data transfers do not receive ACKs. Previous posts to this list have indicated that the suspect was the PXE BIOS (ref "PXELinux can't load the config file?" dated March 20, 2003). Does that still appear to be the case

Hello, I am sure I am not the only person with this problem. I have a list with n elements, each consisting of a single column matrix with different row lengths. Each row has a name ranging from A to E. Here is an example: alph[[1]] A 1 B 2 C 3 D 4 alph[[2]] A 1 C 3 D 4 alph[[3]] A 1 D 4 E 5 I would like to create a matrix from the elements in the list with n columns such that the row names

Hi, I'm trying to use pgamma() within my C application but I'm getting strange results. I have a Debian system with r-mathlib 1.4.1-1 and gcc 2:2.95.4-9. Here are 3 example pgamma() calls executed by R: $ R -q --vanilla < gamma.R > pgamma(98, 100, 1) [1] 0.4333105 > pgamma(21, 100, 5) [1] 0.7002453 > pgamma(2, 100, 69) [1] 0.9997046 > and here is what the small C

Hello, by checking the precision of a convolution algorithm, we found the following "inexactness": We work with R Version 1.8.1 (2003-11-21) on Windows systems (NT, 2000, XP). Try the code: ## Kolmogorov distance between two methods to ## determine P(Poisson(lambda)<=x) Kolm.dist <- function(lam, eps){ x <- seq(0,qpois(1-eps, lambda=lam), by=1) max(abs(ppois(x,

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 =

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

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 0.082372029620717283. When I check these numbers using pgamma, I get: pgamma(1,5e-101, lower.tail=FALSE) =

Hi Developers, The alpha, compiles successfully, but it is failing make check-all (on two seperate machines, both FreeBSD 6.1). Here is the version string: platform i386-unknown-freebsd6.1 arch i386 os freebsd6.1 system i386, freebsd6.1 status alpha major 2 minor 3.0 year 2006 month 03 day 27 svn rev

Hi R-users, I have this code to uniformise the data using gamma: > length(dp1) [1] 696 > dim(dp1) [1] 58 12 > dim(ahall) [1]  1 12 > dim(bhall) [1]  1 12 > trans_dt <- function(dt,a,b) + { n1 <- ncol(dt) +   n2 <- length(dt) +   trans  <- vector(mode='numeric', length=n2) +   dim(trans) <- dim(dt) +   for (i in 1:n1) +   {  dt[,i] <- as.vector(dt[,i])

I've rolled up R-1.9.0.tgz a short while ago. This is a new version with a number of new features, most notably a substantial reorganization of the standard packages, a major update of the grid package, and the fact that underscore can now be used as a regular character in variable names. See below for further changes. Because of the disturbances at the machine that hosted the CVS archives,

I've rolled up R-1.9.0.tgz a short while ago. This is a new version with a number of new features, most notably a substantial reorganization of the standard packages, a major update of the grid package, and the fact that underscore can now be used as a regular character in variable names. See below for further changes. Because of the disturbances at the machine that hosted the CVS archives,

I am not sure whether I'm doing something wrong or there is a bug in the documentation of ks.test. Following the posting guide, as I'm not sure, I haven't found this in the bug tracker, and the R FAQ says that stats is an Add-on package of R, I think this is the place to send it. ?ks.test provides the example <QUOTE> # Does x come from a shifted gamma distribution with shape 3

Dear R experts, I'm trying to call 'pchisq' from within a C subroutine. The following error is returned: ** NON-convergence in pgamma()'s pd_lower_cf() f= nan. This error message is not printed the first time I call 'pchisq' from the C subroutine, but the second time or the next time I call 'pchisq' from within R. My session output is shown below:

Hi! I fairly new to R, have only done pretty basic things so far, so this may be a very basic question..... But I did search the forums and didn't see a solution.... I'm trying to get going with kripp.alpha(). I'm loading data from a file, like this: > library(irr) Loading required package: lpSolve > x <- read.table("foo", comment.char="#", header=TRUE,

x <- c( "a1", "a10", "a2" ) y <- c( "b10", "b2", "a12", "ca1" ) DF <- expand.grid( x = x, y = y ) # randomize set.seed( 42 ) DF <- DF[ sample( nrow( DF ) ), ] # missing from gtools mixedrank <- function( x ) { seq.int( length( x ) )[ gtools::mixedorder(x) ] } o <- do.call( order, lapply( DF, mixedrank ) )

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've got the next problem: I've got this *function*: fitcond=function(x,densfun,pcorte,start,...){ myfn <- function(parm,x,pcorte,...) -sum(log(dens(parm,x,pcorte,...))) Call <- match.call(expand.dots = TRUE) if (missing(start)) start <- NULL dots <- names(list(...)) dots <- dots[!is.element(dots, c("upper",