similar to: In the OPTIM message....

hi all i dont understand the error message that is produced by the optim function. can anybody help??? ie: [[1]]$message [1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH" can anyone help? ########################################################################### SK.FIT(XDATA=a,XDATAname="a",PHI1=1,v=5,vlo=2,vhi=300,phi2lo=.01) [[1]] [[1]]$par [1] -0.01377906

Hi there, I am trying to use linear regression to solve the following equation - y <- c(0.2525, 0.3448, 0.2358, 0.3696, 0.2708, 0.1667, 0.2941, 0.2333, 0.1500, 0.3077, 0.3462, 0.1667, 0.2500, 0.3214, 0.1364) x2 <- c(0.368, 0.537, 0.379, 0.472, 0.401, 0.361, 0.644, 0.444, 0.440, 0.676, 0.679, 0.622, 0.450, 0.379, 0.620) x1 <- 1-x2 # equation lmFit <- lm(y ~ x1 + x2) lmFit Call:

Dear R-help group, I have to maximize a likelihood with 40 parameters and I want to compare the MLE given by "nlminb" (Splus2000, on Windows) with those given by "optim" (R, on Unix). 1) On Splus, The algorithm "nlminb" seems to converge (the parameters stabilize) , it stops after several iterations ( around 400) with the message :"FUNCTION EVALUATION LIMIT

R-help, I'm just trying to find the ML (maximum likelihood) estimates of the mean and standard deviation of a set of observations: >xx=c(2.5,3.5,4,6,6.5,7.5) fn<-function(params,x=xx) { media<-params[1] st <-params[2] pdf=-sum(dnorm(log(xx),log(media),st,TRUE)) return(pdf) } optim(c(mu,stdev),fn,method="L-BFGS-B",lower=c(0.001, 0.001) ,upper = rep(Inf, 2),

R users; A question about optimization within R. I've been using both optim() and nlminb() to estimate parameters and all seems to be working fine. For context (but without getting into specifics - sorry), I'm working with a problem that is known to have correlated parameters, and parameter estimation can be difficult. I have a question on optim() - I'm using

Hi! I'm trying to figure out how to use optim... I get some really strange results, so I guess I got something wrong. I defined the following function which should be minimized: errorFunction <- function(localShifts,globalShift,fileName,experimentalPI,lambda) { lambda <- 1/sqrt(147) # error <- abs(errHuber(localShifts,globalShift, #

I am having trouble with optim. It claims to have converged to a minimum, yet it has in the course of the optimization visited many points which are closer to optimal. I would be grateful for any explanation of this behaviour. I'm trying to estimate the parameters in the model X ~ Binomial(1,p) * NegBin(mu,theta). So I define a log likelihood function, and invoke optim thus: o <- optim

Dear R-devel During the last half a year I have several times encountered the following problem with optim() when using method= "L-BFGS-B". The function return a value which is clearly not the maximum (seen from printing the value each time the function is called). Some output is shown below. A few things I have observed (as I remember it): a. The problem seems to occur when the

Dear all, I am trying to optimize a logistic function using optim, inside the following functions: #Estimating a and b from thetas and outcomes by ML IRT.estimate.abFromThetaX <- function(t, X, inits, lw=c(-Inf,-Inf), up=rep(Inf,2)){ optRes <- optim(inits, method="L-BFGS-B", fn=IRT.llZetaLambdaCorrNan, gr=IRT.gradZL, lower=lw, upper=up, t=t, X=X)

R-help, I'm trying to estimate some parameters using the Maximum Likehood method. The model describes fish growth using a sigmoidal-type of curve: fn_w <- function(params) { Winf <- params[1] k <- params[2] t0 <- params[3] b <- params[4] sigma <- params[5] what <- Winf * (1-exp(- k *(tt - t0)))^b

Hello, S-plus and R helpers,(sorry for cross-post) I wrote some simple C code for one likelihood to be optimized (using optim(MASS)). I use same function, same data, same starting points and same DLL in R and S-plus for comparison. (I compiled it with 'Rcmd SHLIB likelihood.c' and the header files of it include only R.h and math.h). While it works quite fine in S-plus, it forever returns

Hello, I have been trying for weeks to compile a 64-bit Rblas. I started with ATLAS where I have had success in the past, but 64 bit was not behaving, and as each compilation takes between 9 and 12 hours, "test, check, and revise" was not going to be really viable. I therefore switched to OpenBLas (OPBL). I was successful in compiling R-3.0.1 and an OPBL-based BLAS for Windows 64bit

Hi R-users, I am trying to estimate function parameters using optim(). My count observations follows a Poisson like distribution. The problem is that I wanna express the lambda coefficient, in the passion likelihood function, as a linear function of other covariates (and thus of other coefficients). The codes that I am using (except data frame) are the following (FYI the parameters need to be

Hello, I'm facing a problem, using "optim" packeg. I've written a program and run it using the latest R version 2.8.1,but there was an error message as following: R version 2.7.2 (2008-08-25) # same result when I use R version 2.8.1,Copyright (C) 2008 The R Foundation for Statistical ComputingISBN 3-900051-07-0R is free software and comes with ABSOLUTELY NO WARRANTY.You are

Hi, I am using optim with a L-BFGS-B method to minimize a function. As I've understood, the way to specify a tolerance for stopping optimization is through "factr" argument. My function, is by construction, minimal when equal to 1. I wonder if there is any way to pass this info to "optim". If not, how "factr" argument works (I am quite confused about the

Dear All, I am trying to solve the optimization problem below, but I am always getting the following error: Error in optim(rep(20, nvar), f, gr, method = "L-BFGS-B", lower = rep(0, : L-BFGS-B needs finite values of 'fn' Any ideas? Thanks in advance, Paul ----------------------------------------------- k <- 10000 b <- 0.3 f <- function(x) { n <- length(x)

Hi I am doing several mle and want to store them in a list (or whatever is the right construct) to be able to analyse them later. at the moment I am doing: f <- list() f$IP <- mle(...) f$NE <- mle(...) but when I say: > summary(f) I get: Length Class Mode IP 0 mle list NE 0 mle list I don't get the output I would have, i.e. the one from >

Can anyone help me with lbfgsb (function for optimization)? It takes the following parameters: void lbfgsb (int n, int lmm, double *x, double *lower, double *upper, int *nbd, double *Fmin, optimfn fn, optimgr gr, int *fail, void *ex, double factr, double pgtol, int *fncount, int *grcount, int maxit, char *msg, int trace, int nREPORT); What do I put for parameter ex (11th parameter)? I looked at

Dear all I'm having some trouble with a bound-constrained optimization using optim(...,method="L-BFGS-B"). Usually, everything works fine, but for some simulations, the algorithm just gets stuck. When I let my function (+gradient) evaluation print out the function value, I see that L-BFGS-B keeps calling the function with arguments giving the same function value (up to at least

#optim package estimate<-optim(init.par,Linn,hessian=TRUE, method=c("L-BFGS-B"),control = list(trace=1,abstol=0.001),lower=c(0,0,0,0,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf),upper=c(1,1,1,1,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf)) #nlminb package estimate<-nlminb(init.par,Linn,gr=NULL,hessian=TRUE,control =