similar to: error messages

I have started using the circular package but it is not recognizing the function arrows.circular. I attempted to use the example provided in the circular manual. Here is the example code using the circular package: plot(rvonmises(10, circular(0), kappa=1)) arrows.circular(rvonmises(10, circular(0), kappa=1)) arrows.circular(rvonmises(10, circular(0), kappa=1), y=runif(10), col=2)

On 2009-02-24 03:28, Kshitij Sudan wrote: > I am new to LLVM, and I'm trying to compile llvm and llvm-gcc from > subversion on a Solaris10/SPARC machine. I have already tried building > llvm-2.4 on this machine, but it failed. > > I then tried the subversion sources (rev. # 65253 fro llvm and > rev#65263 for llvm-gcc) and llvm at least builds correctly ( I however > have

Hi R-users,   I have this code here: library(numDeriv)   fprime <- function(z) { alp  <- 2.0165;   rho  <- 0.868;   # simplified expressions   a      <- alp-0.5   c1     <- sqrt(pi)/(gamma(alp)*(1-rho)^alp)   c2     <- sqrt(rho)/(1-rho)   t1     <- exp(-z/(1-rho))   t2     <- (z/(2*c2))^a   bes1   <- besselI(z*c2,a)   t1bes1 <- t1*bes1   c1*t1bes1*t2 }   ## Newton

Hi, I am trying to figure out the observed acceptance rate and M, using generalised rejection sampling to generate a sample from the posterior distribution for p. I have been told my code doesn't work because I need to "take the log of the expression for M, evaluate it and then exponentiate the result." This is because R is unable to calculate high powers such as 545.501. As

I am new to LLVM, and I'm trying to compile llvm and llvm-gcc from subversion on a Solaris10/SPARC machine. I have already tried building llvm-2.4 on this machine, but it failed. I then tried the subversion sources (rev. # 65253 fro llvm and rev#65263 for llvm-gcc) and llvm at least builds correctly ( I however have not tried testing it!). I can execute binaries located in

Hi, R guys: I'm using L-BFGS-B method of optim for minimization problem. My function called besselI function which need non-negative parameter and the besselI will overflow if the parameter is too large. So I set the constraint box which is reasonable for my problem. But the point outside the box was test, and I got error. My program and the error follows. This program depends on CircStats

Hi, I am trying to figure out the observed acceptance rate and M, using generalised rejection sampling to generate a sample from the posterior distribution for p. I have been told my code doesn't work because I need to "take the log of the expression for M, evaluate it and then exponentiate the result." This is because R is unable to calculate high powers such as 545.501.

#bug 1: besselI() for nu<0 and expon.scaled=TRUE #tested with R-devel (2007-06-17 r41981) x <- 2.3 nu <- -0.4 print(paste(besselI(x, nu, TRUE), "=", exp(-x)*besselI(x, nu, FALSE))) #fix: #$ diff bessel_i_old.c bessel_i_new.c #57c57 #< bessel_k(x, -alpha, expo) * ((ize == 1)? 2. : 2.*exp(-x))/M_PI #--- #> bessel_k(x, -alpha, expo) * ((ize == 1)? 2. :

Hi r-users,   I would like to solve for z values using newton iteration method.  I 'm not sure which part of the code is wrong since I'm not very good at programming but would like to learn.  There seem to be some output but what I expected is a vector of z values.  Thank you so much for any help given.   newton.inputsingle <- function(pars,n) {  runi    <- runif(974, min=0, max=1)

Dear OpenSSH gurus, My machine is running Red Hat Linux 6.1 and has installed all of the 6.binary rpms generated from the source rpms openssh-2.2.0p1-2.src.rpm 6.and openssl-0.9.5a-3.src.rpm. When I use protocol version 2 (by specifying "Protocol 2,1" in ~/.ssh/config), I can establish connections properly, but they do not shut down properly. When I run a remote command by "ssh

Hi R-users,   I wrote a code to evaluate double sum as follows:   ff2 <- function(bb,eta,z,k) { r <- length(z) for (i in 1:r) { sm1 <- sum((z[i]*bb/2)*(psigamma((0:k)+eta+1,deriv=0)/(factorial(0:k)*gamma((0:k)+eta+1))))  sm2 <- sum((besselI(z[i]*bb,eta)*log(z[i]*bb/2) - sm1)/besselI(z[i]*bb,eta))  sm2 } ff2(bb,eta,z,10)     but it gave me the following message:   >

Hi r-users,   I hope somebody can help me with this code. I would like to solve for z values using newton iteration method.  I 'm not sure which part of the code is wrong since I'm not very good at programming but would like to learn.  There seem to be some output but what I expected is a vector of z values.  Thank you so much for any help given.   newton.inputsingle <-

Hello, I am trying to compute MLE for non-Gaussian AR(1). The error term follows a difference poisson distribution. This distribution has one parameter (vector[2]). So in total I want to estimate two parameters: the AR(1) paramter (vector[1]) and the distribution parameter. My function is the negative loglikelihood derived from a mixing operator. f=function(vector)

Hi, I'm trying to compile two functions into one function. the first funtion is called 'fs' which is self-made function, another function is from the built-in 'integration' function that is copy-paste-edited. If built separatey, these functions work well. However that is not the case if combines together, where certainly I made mistake somewhere when constructing the code.

Hello everybody. I would like to pose a question regarding a warning message after running a function of my own. The function I created for computing the p-value of the dw statistic has a command line like this: »dwf0 <- function(dw,eigen) { carfun <- function(x) { (prod(1+2*(eigen-dw)*1i*x)^(-1/2)-prod(1-2*(eigen-dw)*1i*x)^(-1/2))/(1i*x) } ; 1/2+integrate(f=carfun,lower = 0,upper =

Hi, I have written out the log-likelihood function to fit some data I have (called ONES20) to the non-central chi-squared distribution. >library(stats4) >ll<-function(lambda,k){x<-ONES20; 25573*0.5*lambda-25573*log(2)-sum(-x/2)-log((x/lambda)^(0.25*k-0.5))-log(besselI(sqrt(lambda*x),0.5*k-1,expon.scaled=FALSE))} > est<-mle(minuslog=ll,start=list(lambda=0.05,k=0.006))

Dear all, I have some issues with integrate in R thus I would like to request your help. I am trying to calculate the integral of f(x)*g(x). The f(x) is a step function while g(x) is a polynomial. If f(x) (step function) changes its value only few times (5 or 6 'steps') everything is calulated ok(verified results in scrap paper) but if f(x) takes like 800 different values I receive the

> version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 7.1 year 2003 month 06 day 16 language R Bug: integrate(f,lower,upper,extra_args) where f <- function(x,extra_args) { body } integrate doesn't pass the extra arguments when calling f. As a first check of this finding I integrated dnorm from

I have been told by the CRAN administrators that the following code generated an error on 64-bit Fedora Linux (gcc, clang) and on Solaris machines (sparc, x86), but runs well on all other systems): > fn <- function(x, y) ifelse(x^2 + y^2 <= 1, 1 - x^2 - y^2, 0) > tol <- 1.5e-8 > fy <- function(x) integrate(function(y) fn(x, y), 0, 1,

Hello, Rlisters I have to compute p-values that are on the tail of the distribution, P-values < 10^-20. However, my current implementations enable one to estimate P-values up to 10^-12, or so. A typical example is found below, where t is my critical value. ########### example - code adapted from Rassoc ####################### rho01 = 0.5 rho105 = 0.5 rho005 = 0.5 t = 8 z = 2