similar to: Two or more dimensional root (Zero) finding

Dear R-users, I am trying to port to R something that I wrote in Matlab to perform model parameter optimization using the Nelder-Mead simplex method (fminsearch). I read the help on ?optim (which seems to be the way to go) as well as a bunch of posts on the topic, but I would like to make sure about something before I spend to much time trying to reproduce something that is not possible. The

I have some binaries I would like to distribute with a package (I am not the original author; I have the source code but can't distribute it because it contains _Numerical Recipes_ code. The long-term solution is to replace the code with new code written in R, or in clean C, but in the meantime ...) I'm uncertain both where they ought to go and where they will work (and hoping there

Hello, for my diploma thesis I need to program a solver for Merton?s respectively Black?s and Scholes? Option pricing formula, which should be achieved for several dates. What I want to do is to estimate the value of a firm?s assets "vA" (x[2] denotes vA) and the option-implied volatility of firm?s assets "sigA" (x[1] denotes sigA) by solving it simultaneous using the Black

Hi, I'm a newcomer to R, having previously used SPSS. One problem I have run into is computing kurtosis. A test dataset is here: http://www.whinlatter.ukfsn.org/2401.dat > library(moments) > data <- read.table("2401.dat", header=T) > attach(data) > loglen <- log10(Length) With SPSS, I get Skewness -0.320 Kurtosis -1.138 With R: > skewness(loglen) [1]

I'm a very recent user of R. I have been adapting my Splus programmes and I found only one (important) problem. There exists no function "nlmin" in R and its substitute, "nlm", does not work well with my kind of problems, sometimes no achieving convergence, other tines "converging" to impossible values. My models are highly nonlinear and are to be estimated by

Dear all, I am using the functions 'optim' and 'nlminb'. For both, you can provide a function which computes the gradient of the objective function (to enhance speed and precision). In my case, both the objective function and the gradient take time to be computed and share many common computations (similar matrix, products, etc...). Therefore, I have to compute these

I have two matrix s1 and s2, each of them is 1000*1. and I have two equations: digamma(p)-digamma(p+q)=s1, digamma(q)-digamma(p+q)=s2, and I want to sovle these two equations to get the value of x and y, which are also two 1000*1 matrices. I write a program like this: f <- function(x) { p<- x[1]; q <- x[2]; ((digamma(p)-digamma(p+q)-s1[2,]) )^2 +((digamma(q)-digamma(p+q)-s2[2,]) )^2

Hello again Is there any way (or an alternative non-linear minimiser) that arguments to the function called in nlm can be passed in version 0.62.4? Like (I believe) nlmin in a well known other program or optimise in R. Do we use global variables? Shurely not! \John -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi I would like to solve a system of nonlinear equations below using dfsane function   mn <- 142.36; vr <- 9335.69 ; sk <- 0.81;  kur <- 0.25 test_fn <- function(p) {    f <- rep(NA, length(p))     f[1] <- p[1]*(p [2]+p[3])- mn   f[2] <- - vr + 2*p[1]*p[2]*p[3]*(p[4]-1)+p[1]*(p[2]+p[3])^2   f[3] <- - sk + (p[1]*(p [2]+p[3])^3*(p[1]+1)*(p[1]+2)-6*p[1]*p[2]*p[3]*(p[2]+

Dear R users, I am trying to minimise a function using "nlm". I am getting the following error message: "Error: function is too long to keep source" The function is really very long (about 100 A4 pages). Is there anything I could do to solve this problem? At the moment I am using "nlmin" in S-Plus with no problems but I'd prefer to use R. Thank you very

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

Dear R users, I have two nonlinear equations, f1(x1,x2)=0 and f2(x1,x2)=0. I try to use optim command by minimize f1^2+f2^2 to find x1 and x2. I found the optimal solution changes when I change initial values. How to solve this? BTW, I also try to use grid searching. But I have no information on ranges of x1 and x2, respectively. Any suggestion to solve this question? Thanks, Kate

Hello R users, I am trying to estimate the parameters of a bimodal normal distribution using moments matching, so I have to solve a non-linear system of equations. How can I solve the following simple example? x^2 - y^2 = 6 x ? y = 3 I heard about nlsystemfit, but I don?t know how to run it exactly. I have tried the following code, but it doesn?t really work: f1 <-y~ x[1]^2-x[2]^2-6 f2

Dear all, I think I must be going crazy.... If I do > mean(rpois(1000000, 14)) I get: [1] 13.50420 and again: > mean(rpois(1000000, 14)) [1] 13.49896 > mean(rpois(1000000, 14)) [1] 13.50161 > mean(rpois(1000000, 15)) [1] 14.49250 > mean(rpois(1000000, 15)) [1] 14.49897 > mean(rpois(1000000, 14.5)) [1] 13.99689 > mean(rpois(1000000, 14.5)) [1] 13.9963 This was on a platform

I have the following function for which I need to find the root of a: f <- function(R,a,c,q) sum((1 - (1-R)^a)^(1/a)) - c * q To give context for the problem, this is a psychometric issue where R is a vector denoting the percentage of students scoring correct on test item i in class j, c is the proportion correct on the test by student k, and q is the number of items on the test in total. I

Hi r-users, I would like to solve system of nonlinear equation using BBsolve function and below is my code.  I have 4 parameters and I have 4 eqns. mgf_gammasum <- function(p) { t  <- rep(NA, length(p)) mn <- 142.36 vr <- 9335.69 sk <- 0.8139635 kur <- 3.252591 rh  <- 0.896 # cumulants k1 <- p[1]*(p[2]+p[3]) k2 <- p[1]*(2*p[2]*p[3]*p[4] +p[2]^2+p[3]^2) k3 <-

Dear Partecipants to the list, I am Enrico Foscolo, a student of the Faculty of Statistics, University of Bologna, and I am interested under consideration of the search of zeros of one function. I would want to write a code using the software R. I have already read the book "Computing the Zeros of Analytic Functions" (P. Kravanja and M. Van Barel, 2000) that speaks about this problem,

Hi all, I have a system of 3 equations with many defined parameters and 3 variables I need to find solutions to. I actually know the solutions I'm aiming for (0.07,0.287,0.0061) but R tends to give me (0,0,0). I tried the "BB" package but don't really follow how to refine my solutions from that; these are wrong so far. Here's my code from trying that: > f<-function(x){

Hi, I'd like to know if the Holt-Winters function in R can modify the alpha paremeter in an "intelligent" way. I know it can vary from 0 to 1. Wich mathematical formula does it use to calculate the correct value of alpha? Thanks, bye. Carlo

Dear Gregory R. Warnes, I'm a phd student in statistics, at the University of Milano Bicocca. I'm interested to the methods of estimate the parameters of the Dirichlet distribution. Do you have implemented an algorithm in R? If so, can you give me the script? or, in general, some helps? Best Regards Gianna --------------------------------------------------------------- Gianna Monti