similar to: choose fails a fundamental property of binomial coefficients (PR#11035)

Full_Name: Jerry W. Lewis Version: 2.6.1 OS: Windows XP Professional Submission from: (NULL) (24.147.191.250) pchisq(0,0,ncp=lambda) returns 0 instead of exp(-lambda/2) pchisq(x,0,ncp=lambda) returns NaN instead of exp(-lambda/2)*(1 + SUM_{r=0}^infty ((lambda/2)^r / r!) pchisq(x, df + 2r)) qchisq(.7,0,ncp=1) returns 1.712252 instead of 0.701297103 qchisq(exp(-1/2),0,ncp=1) returns 1.238938

Full_Name: Jerry W. Lewis Version: 2.10.1 OS: Windows XP Professional Submission from: (NULL) (198.180.131.21) In the line "The quantile is right continuous: qpois(q, lambda) is the smallest integer x such that P(X <= x) >= q." "q" is used as a probability when the Arguments section defines it to be a quantile. Also there are some representation problems where the

I am writing to ask if R has a build- in function to calculate this polylogarithm Li_n(z) function , also known as the Jonqui?re's function defined as Li_n(z)=sum_(k=1)^infty(z^k)/(k^n) Thanks Andy

Full_Name: Jerry W. Lewis Version: 2.7.0 OS: Windows XP Professional Submission from: (NULL) (198.180.131.16) If you are saying that there is no need to solve for the noncentrality parameter, please justify this amazing assertion. If you are saying that this need is already adequately addressed in R, then please enlighten me.

Hi All, I am trying to use A Gaussian quadrature over the interval (-infty,infty) with weighting function W(x)=exp(-(x-mu)^2/sigma) to estimate an integral. Is there a way to do it in R? Is there a function already implemented which uses such weighting function. I have been searching in the statmode package and I found the function "gauss.quad(100, kind="hermite")" which uses

Hi, dear R users I am a newbie in R and I wantto use the method of meximum likelihood to fit a Weibull distribution to my survival data. I use "optim" as follows: optim(c(1, 0.25),weibull.like,mydata=mydata,method="L-BFGS-B",hessian = TRUE) My question is: how do I setup the constraints so that the two parametrs of Weibull to be pisotive? Or should I use other function

Full_Name: Jerry W. Lewis Version: 2.6.2 OS: Windows XP Professional Submission from: (NULL) (198.180.131.16) choose() returns incorrect values for all fractional arguments, regardless of sign. It returns 0 when both arguments are negative integers, which is not always correct (as in some formulations of the negative hypergeometric). Examples (correct answers from Maple's binomial

choose(-5,-7) uses integer arguments (as specified in Help) and returns a numeric value that is incorrect. Either the function or the documentation should be fixed. If the function is not fixed, a warning or an error would be helpful. The fact that choose(n,k) usually returns choose(n,round(k,0)) is not obvious from either the output or the documentation. I suggest issuing a warning when

Hello to all, I am having trouble with intregrating a complicated uni-dimensional function of the following form Phi(x-a_1)*Phi(x-a_2)*...*Phi(x-a_{n-1})*phi(x-a_n). Here n is about 5000, Phi is the cumulative distribution function of standard normal, phi is the density function of standard normal, and x ranges over (-infty,infty). My idea is to to use quadrature to handle this integral. But

I have a function written for Splus, when I run it in R I obtain get an error because the function has the elements "0.d0" and "2.d0". How can I change it to run in R? The function can be found in page 230 from http://www.stat.wisc.edu/~mchung/teaching/stat471/stat_computing.pdf Function is as follows: gauher <- function(n) {# Gauss-Hermite: returns x,w so that

Hi, I sometimes play around with extreme parameters for distributions and found that qbeta is not always monotone as the following example shows. I don't know whether this is serious enough to submit a bug report (as this example is near to the limitations of floating point arithmetic). Josef > x <- qbeta((0:100)/100,0.01,5) > x [1] 0.000000e+00 1.253990e-201 1.589622e-171

Hello, I'm quite new to R but tried to learn as much as possible in the last few months. My problem is that I would like to estimate the model of Leon et al. (2005). I have shortly summarised the most important equations in the following pdf file: http://hannes.fedorapeople.org/leon2005.pdf My main question is now how could I introduce these two additional terms into the Likelihood

Hi, Is there a way to simulate a population with R and pull out m samples, each with n values for calculating m means? I need that kind of data to plot a graphic, demonstrating the central limit theorem and I don't know how to begin. So, perhaps someone can give me some tips and hints how to start and which functions to use. thanks for any help, joerg

Hello guys, I am stuck here: How do I make 1000 samples of n = 10 observations from an Exponential distribution and then compute the mean for all those 1000 samples? Basically I need to prove the Central Limit theorem, which states: http://www.nabble.com/file/p22664113/d175f06cbf200bd52a2c27a2e56dc594.png Where the Sn is sum of random variables, n we have from the question, mu is mean and

Full_Name: Robin Hankin Version: 2.4.0 RC OS: MacOSX 10.4.7 Submission from: (NULL) (139.166.242.29) The first cut line described in Trig.Rd for asin() is incorrect in the ascii version of the manpage. The Rd file reads: For \code{asin()} and \code{acos()}, there are two cuts, both along the real axis: \eqn{\left(-\infty, -1\right]}{\(-Inf, 1\]} and Note the inconsistency between the

https://bugs.freedesktop.org/show_bug.cgi?id=54512 Bug #: 54512 Summary: xrandr does not detect screen Classification: Unclassified Product: xorg Version: unspecified Platform: x86-64 (AMD64) OS/Version: Linux (All) Status: NEW Severity: normal Priority: medium Component: Driver/nouveau

Hi, Found CloneBasicBlock utility only does the cloning without any remapping. Consider below example: Input block: sw.epilog: ; preds = %sw.bb20, %sw.bb15, %sw.bb10, %sw.bb6, %sw.bb2, %sw.bb, %while.body, %if.end29 %no_final.1 = phi i32 [ %no_final.055, %while.body ], [ 1, %if.end29 ], [ %no_final.055, %sw.bb20 ], [ %no_final.055, %sw.bb15 ], [

In complex analysis, Cauchy's integral theorem states (loosely speaking) that the path integral of any entire differentiable function, around any closed curve, is zero. I would like to see this numerically, using R (and indeed I would like to use the residue theorem as well). Has anyone coded up path integration? -- Robin Hankin Uncertainty Analyst Southampton Oceanography Centre

Dear All I am totally new to R and I would like to know whether R is able and appropriate to illustrate to my students the Central Limit Theorem, using for instance 100 independent variables with uniform distribution and showing that their sum is a variable with an approximated normal distribution. Thanks in advance, Paul

Having compiled and successfully installed e1071 on a previous machine (and run under 0.62.4) I want to compile it on a new machine to run under 0.63.3 but the loader can't find netpbm - both machined are RH5.2 Linux installations. I have some quite old netpbm's on a CD but none more recent and I certainly didn't install them on my old machine. I can't locate or rpm -q or rpm