similar to: Solving a equation

Dear All, I couple of weeks ago, I’ve asked for a package recommendation for nonlinear optimization. In my problem I have a fairly complicated non-linear objective function subject to one non-linear equality constrain. I’ve been suggested to use the *Rdonlp2* package, but I did not get any results after running the program for 5 hrs. Is it normal to run this type of programs for hours? Also,

Hi, I am trying to find a simple way to numerically solve a system of two equations equal to zero with two unknowns (x_loc and y_loc). Here is a mock data set and below it, the equations I need to solve. theta<-c(180,135,90)/(2*pi) x<-c(0,0,15) y<-c(20,0,0) 0 = -sum((y_loc-y)*(sin(theta)*(x_loc-x)-cos(theta)*(y_loc-y))/(((x_loc-x)^2+(y_loc-y)^2)^0.5)^3) 0 =

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

Hi, Is this method broken in R? I am using it to find roots of the following function: f(x) = 2.5*exp(-0.5*(2*0.045 - x)) + 2.5*exp(-0.045) + 2.5*exp(-1.5*x) - 100 It is giving an answer of -38.4762403 which is not even close (f(x) = 2.903809e+25 for x=-38.4762403). The answer should be around 0.01-0.1. This function should converge.. Even for a simple function like f(x) = exp(-x) * x, it gives

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 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 <-

Hi there, I would like to solve the following equation in R to estimate 'a'. I have the amp, d, x and y. amp*y^2 = 2*a*(1-a)*(-a*d+(1-a)*x)^2 test data: amp = 0.2370 y= 0.0233 d= 0.002 x= 0.091 Can anyone suggest how I can set this up? Thanks, Diviya [[alternative HTML version deleted]]

Dear All, I need to find the (possible multiple) zeros of a function f within an interval. I gave uniroot a try, but it just returns one zero and I need to provide it with an interval [a,b] such that f(a)f(b)<0. Is there any function to find the multiple zeros of f in (a,b) without constraints on the sign of f(a) and f(b)? Many thanks Lorenzo

People, I'm researching some Bayesian statistic topics and in the midle of my study i found a very simple problem and i'm trying to find a simple package to solve this type of equations: Lets say that i need to compute beta values for the beta distribution and i now for example: E(teta)=a/(a+b) = 0,5 Var(teta)=ab/((a+b)^2(a+b+1))=0.05 So if i want to solve this to non-linear system to

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

I'm trying to solve a system of 3 equations as part of a sub-routine in R, ie first eqn a/x-b*sqrtx+c=log(1/dx+1/e(sqrtx); snd eqn (f*y)/z-g/y-h=-log(2/x+(z/y)/(i*x) and third eqn is of the form zz=x/(j-k(z/y) where a..k inclusive are constants, x,y,z and zz are inputs. How can this be done in R? [[alternate HTML version deleted]]

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 +

Dear all, I am relatively new to R and have had some difficulty in understanding the user manual for a package that I have downloaded to evaluate non-linear simultaneous equations. The package is called systemfit. Does anyone have any experience of this package? What I am trying to do is solve a non linear simultaneous equations... Could anyone give me an example (please) of the code that

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

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

Dear R-users, I use the "nleqslv" function to get parameter estimates by solving a system of non-linear equations. But I also need standard error for each of estimates. I checked the nleqslv manual but it didn't mention about SE. Is there any way to get the SE for each estimate? Thank you very much. [[alternative HTML version deleted]]

I'm solving 4 complex equations simultaneously. Code is below. The code returns only zero's for the solution though there should also be a non-zero result. I'm pretty confident that the equations are correct because they are straight from a published paper and I checked them pretty thoroughly. The parameter values I used are from the published paper as well. Any suggestions for how

Surprisingly, I played around with some test code and below actually creates equations that look correct. tempmat<-matrix(10,nrow=6,ncol=6) restrictmat<-diag(6) colnames(tempmat)<-c("AUD.l1","CHF.l1","CAD.l1","GBP.l1","EUR.l1","JPY.l 1")

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 all, I am relatively new to R and have had some difficulty in understanding an error i get when running a code to solve a system of non-linear equations, with four equations and two variables. This is my code: ALPHA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) BETA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) GAMMA <- c(0.3940672148378, 0.1, 0.15,