similar to: Solving a system of nonlinear equations involving weighted parameters

Dear all, I just know how to solve an eaquation by using optim() or nlm(). But, now, I have three nonlinear equations, how could we use optim() or nlm() to solve  a system of nonlinear equations in R?  Thank you so much. Sincerely, Joe ___________________________________________________ 您的生活即時通 － 溝通、娛樂、生活、工作一次搞定！ [[alternative HTML version deleted]]

What is the "classic" R function for solving a (possibly over determined) system of non-linear equations? Thank you! Moshe Olshansky e-mail: moshe.olshansky@brevanhoward.com The information transmitted is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or

After many months, I am now banging my head against the wall because I can't find a solution to this seemingly trivial problem.  Any help would be appreciated: I am trying to apply a nonlinear fitting routine to a 3D MR image on a voxel-by-voxel basis.  I've tested the routine using simulated data and things went well.  As for the real data, the fitting routine

Hey, I was wondering if there existed a R function similar to 'fsolve' or 'fzero' Matlab functions? Thanks! Francois Aucoin [[alternative HTML version deleted]]

Dear: I am having trouble solving simultaneous nonlinear equations by R. I have been using BBsolve (BB) to do so. Though the function is very strong, still the program doesn't converge. I have tried all (according to my small knowledge) the options described in the help file. Now I am trying to find something else than BBsolve for solving simultaneous nonlinear equations by R. Any idea or

Hello there, I wish to solve the following nonlinear System of equations: + u1 - Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) - Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) == 0 + u2 - Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) - Vmax21*S2/( S2 + Km21 *(1+S1/Km11)) == 0 + Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) + Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) - d1*P1 == 0 + Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) + Vmax21*S2/( S2 +

Hi, We (Paul Gilbert and I) have just released a new R package on CRAN called "BB" (stands for Barzilai-Borwein) that provides functionality for solving large-scale (and small-scale) nonlinear system of equations. Until now, R didn't have any functionality for solving nonlinear systems. We hope that this package fills that need. We also have an implementation of the

Hello there Can anybody please tell me if there is any package in R to solve the following 4 nonlinear equations with 4 unknowns: alpha*exp(20/sigma)+ beta*exp(21/tau) = 2 alpha*exp(22/sigma)+ beta*exp(9/tau) = 4 alpha*exp(10/sigma)+ beta*exp(30/tau) = 6 alpha*exp(40/sigma)+ beta*exp(39/tau) = 5 where alpha = exp(lambda/sigma) beta= exp(delta/tau) I need to estimate lambda, sigma, delta, tau

I am trying to fit a nonlinear model using nlm(). My application of nlm() is a bit complicated. Here is the story behind the model being fit: The observer is trying to detect a signal corrupted by noise. On each trial, the observer gets stim=signal+rnorm(). In the simulation below I have 500 trials. Each row of stim is a new trial. On each trial, if the cross-correlation between the stim and the

GENERAL REFERENCE ON NONLINEAR OPTIMIZATION? What are your favorite references on nonlinear optimization? I like Bates and Watts (1988) Nonlinear Regression Analysis and Its Applications (Wiley), especially for its key insights regarding parameter effects vs. intrinsic curvature. Before I spent time and money on several of the refences cited on the help pages for "optim",

Thanks very much Douglas for the pointer to nlm. Maybe the "Notes on R" maintainer can add at least a mention of nlm in the section on nonlinear fitting? I never did nonlinear fitting in S-Plus before, so I have nothing to unlearn, but I was hoping someone could show me how to do a least squares fit with nlm. example: x<-c(1,2,3,4,5,6) y<-.3*x^-.6 +.2 y<-y+rnorm(6,0,.01)

Thanks very much Douglas for the pointer to nlm. Maybe the "Notes on R" maintainer can add at least a mention of nlm in the section on nonlinear fitting? I never did nonlinear fitting in S-Plus before, so I have nothing to unlearn, but I was hoping someone could show me how to do a least squares fit with nlm. example: x<-c(1,2,3,4,5,6) y<-.3*x^-.6 +.2 y<-y+rnorm(6,0,.01)

Hi, I would appreciate if someone could help me on track with this problem. I want to compute some parameters from a system of equations given a number of sample observations. The system looks like this: sum_i( A+b_i>0 & A+b_i>C+d_i) = x sum_i( C+d_i>0 & C+d_i>A+b_i) = y sum_i( exp(E+f_i) * ( A+b_i>0 & A+b_i>C+d_i) = z A, C, E are free variables while the other

Hi, I want to find a value of n1. I used the following code but I am getting the error - Error in as.vector(x, mode) : cannot coerce type 'closure' to vector of type 'any' n=10 a_g<-(1/(n*(n-1)))*((pi/3)*(n+1)+(2*sqrt(3)*(n-2))-4*n+6) a_s<-function(n1) { t1=(n1-1)/2; (t1*(gamma(t1)/gamma(n1/2))^2)/2-1-a_g } xm<-solve(a_s) Can anyone help me out. Thanks in

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

Dear R users, I am trying to find the mle that involves integration. I am using the following code and get an error when I use the nlm function d<-matrix(c(1,1,0,0,0,0,0,0,2,1,0,0,1,1,0,1,2,2,1,0),nrow=10,ncol=2) h<-matrix(runif(20,0,1),10) integ<-matrix(c(0),nrow=10, ncol=2) ll<-function(p){ for (k in 1:2){ for(s in 1:10){ integrand<-function(x)

Hi, I am relatively new to R and am trying to solve two simultaneous nonlinear equations in two variables numerically, and was wondering if anyone knew if any of the packages could do that. An alternative is writing my own code using Newton-Raphson; I did that but was not able to get good convergence. Any ideas please? Thanks Yogesh [[alternative HTML version deleted]]

Hi all, I would like to ask that is there any function in R which can solve nonlinear system equations with several variables. Thats mean some functions similar to the 'fsolve' or 'fzero' in matlab. Thanks you Jerry _________________________________________________________________ Get 10Mb extra storage for MSN Hotmail. Subscribe Now!

Hello Everybody: I am searching for an R package for fitting Generalized Estimating Equations (GEE) with weights (i.e. Weighted Estimating Equations). From the R documentation I found "geese(geepack)" for fitting Generalized Estimating Equations. In this documentation, under the paragraph “weights” it has been written, “an optional vector of weights to be used in the fitting process.

Dear all, I encounter some discrepancies when comparing the deviance of a weighted and unweigthed model with the AIC values. A general example (from 'nls'): DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) This is the unweighted fit, in the code of 'nls' one can see that 'nls' generates a vector