similar to: newton method for single nonlinear equation

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 <-

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

I would like to solve a nonlinear eqn using newton method and here is the code:   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)  

Hi r-users,   I hope somebody can help me to understand the error message.  Here is my code; ## Newton iteration newton_gam <- function(z) { n   <- length(z)   r   <- runif(n)   tol <- 1E-6   cdf <- vector(length=n, mode="numeric")   fprime <- vector(length=n, mode="numeric")   f   <- vector(length=n, mode="numeric")     for (i in 1:1000)   {

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     <-

I want to generate 1,000 random samples of sample size=1,000 from ZINB. I know there is a rnegbin() to generate random samples from NB, and I know I can use the following process: do i=1 to 1000 n=0 do i=1 to 1000 if runi(1)>0.1 then x(i) = 0; else x(i)=rnegbin(); n=n+1; if n>1000 then stop; end; output; end; Anybody can help me out with the R code? Thanks very much ahead of time.

Hi All. I'd like to generate a sample of n observations from a k dimensional multivariate normal distribution with a random correlation matrix. My solution: The lower (or upper) triangle of the correlation matrix has n.tri=(d/2)(d+1)-d entries. Take a uniform sample of n.tri possible correlations (runi(n.tr,-.99,.99) Populate a triangle of the matrix with the sampled correlations Mirror the

Hi Francois, Thank you for your interest. I tried the card alone so I don't think is an IRQ problem (anyway is there a way to be sure?) To be sincere, in all systems I saw (even working ones) there is an IRQ balance failed where Linux boots. The system is new, I tried different processors (P4 and Celeron) with SMP kernel and without. The card has the echo module, could not be

I'm runiing wine-20031212 on a dual boot machine. I have both win98 and w2k installed. Other posts have suggested these be copied. Is the the right - complete? -set? advapi32.dll comctl32.dll ddraw.dll gdi32.dll kernel32.dll mfc42.dll msvcrt.dll ole32.dll rpcrt4.dll shell32.dll shlwapi.dll user32.dll sean

Hello, I am try to get my "new" UPS running with NUT on my OpenMediaVault device but only receive error meassages on several configurations I try. Your support is really appreciated for getting it solved. Best Regards, Olaf *lsusb* Bus 002 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 006 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 001 Device 001: ID

For reference, the case with a variable loop count is filed as PR27894: https://llvm.org/bugs/show_bug.cgi?id=27894 And the case with a constant loop count is filed as PR27899: https://llvm.org/bugs/show_bug.cgi?id=27899 On Thu, Jun 2, 2016 at 7:48 AM, Demikhovsky, Elena via llvm-dev < llvm-dev at lists.llvm.org> wrote: > I implemented IV simplification with FP SCEV and uploaded a new

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

#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 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:   >

In order to fit a probability distribution proposed by Sichel [Journal of the Royal Statistical Society. Series A (General), Vol. 137, No. 1. (1974), pp. 25-34], I need a modified Bessel function of the 2nd kind. I notice that the base package of "R" only has modified Bessel functions of the 1st and 3rd kind. Does a modified Bessel function of the 2nd kind exist anywhere? Many

Dear R-Group: Recently, I ran into a problem. I was using a function called "I.1", which evaluates the first-order modified Bessel function of the first kind, in the package "CircStats". This function is not vectorized, since it uses a couple of "if" conditions. However, when I called this function with a vector argument, I got no error/warning messages in

Hi R-users, Does R has a topic on newton's method? Thank you for the info.

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 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))

Hello Everybody in order to get some needed results out of my function i need to get my besselI function evaluated at some values which normally gave Inf or 0 (expon.scaled NAN) back. So I would like to increase the range in R from approxamittly 1e+320 to aabout 1e+500 or something like that. Is there any possibility or pacckage to do this easily? Thank You Sebastian Kaiser Institut for Statistics