similar to: Optim

Hi, All: I used optim() to minimise likelihood function for fitting the data to a partiuclar distribution. The function is converged and the value of log-likelihood is different when I change the intial value. Whether it means the program does not work well? Thanks! Xin [[alternative HTML version deleted]]

Hello I have a XP on my Pc ,and I would like to install the splancs package on my machine what is the step for implementing them on my library? --------------------------------- [[alternative HTML version deleted]]

Hello I would like to install a package on R (splancs package) after downloading them what is the step for implementing them in my library? Thank you. --------------------------------- [[alternative HTML version deleted]]

Hi, I have noticed that there is a change in the use of ellipses or . in R versions 2.6.1 and later. In versions 2.5.1 and earlier, the . were always at the end of the argument list, but in 2.6.1 they are placed after the main arguments and before method control arguments. This results in the user having to specify the exact (complete) names of the control arguments, i.e. partial matching is

i want to estimate parameters with maximum likelihood method with contraints (contant numbers). for example sum(Ai)=0 and sum(Bi)=0 i have done it without the constraints but i realised that i have to use the contraints. Without constraints(just a part-not complete): skellamreg_LL=function(parameters,z,design) { n=length(z); mu=parameters[1]; H=parameters[2]; Apar=parameters[3:10];

Hello, I want to find the roots of an equation in two variables. I am aware of the uniroot function, which can do this for a function with a single variable (as I understand it...) but cannot find a function that does this for an equation with more than one variable. I am looking for something implementing similar to a Newton-Raphson algorithm. Thanks. -- Bill Shipley North American Editor for

I am trying to maximise a complicated loglikelihood function with the "optim" command. Is there some way to get to know the estiamtes at each iteration? When I put "control=list(trace=TRUE)" as an option in "optim", I just got the initial and final values of the loglikelihood, number of iterations and whether the routine has converged or not. I need to know the

Hi, my name is Marcel R. Lopes. My problem is, I made a code to calculate the estimates of a Cox model with random effects. Used to optimize the R command for this. The estimates were calculated correctly, but the Hessian matrix does not have good values. The same thing was done in SAS and gave good results for the Hessian Matrix. Where is the problem in R? As the Hessian is calculated?. How

Dear All, Is there any package to do multi-objective optimization? For instance, consider the following problem: maximize f(x,y) in order to x and maximize g(x,y) in order to y, simultaneously, with x and y being the same both for f and g. Can R do it numerically? Thanks in advance, Paul

Dear all When I used the method, L-BFGS-B, in OPTIM, I've got the following message. --------------------------------------------------------------------- $par [1] 0.176166426835580 $value [1] 1322.17600079332 $counts function gradient 8 8 $convergence [1] 0 $message [1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH" $hessian [,1] [1,]

Hi, I am currently trying to execute the following command: f<-factanal(factors=k$Components$nparallel,covmat=m,n.obs=2287,rotation="varimax",control=list(opt=list(method=c("BFGS")))) but keep getting the error: L-BFGS-B needs finite values of 'fn' I can't figure out what I am doing wrong here, why isn't optim being told to use BFGS instead of L-BFGS-B...

I've seen with other software the capability for the optimizer to switch algorithms if it is not making progress between iterations. Is this capability available in optim()? Thanks, Stephen Collins, MPP | Analyst Health & Benefits | Aon Consulting [[alternative HTML version deleted]]

[sorry, forgot some details...] I'm using optim(param, fun, method='L-BFGS-B', lower=lo, upper=up) to minimize a certain function. Often the minimization ends with the message: ERROR: ABNORMAL_TERMINATION_IN_LNSRCH What is optim() trying to say? What have I to change in my function to make the minimization succeed? Do you think using BBoptim() instead of optim() changes anything?

Dear R user I follow the steps defined in Modern applied statistics page(453) to use optim. However, when I run the following code the parameters seems way off and the third parameter(p3) stayed as the initial value. below is the code: ## data da=c(418,401,416,360,411,425,537,379,484,388,486,380,394,363,405,383,392,363,398,526) ### initial values pars=c(392.25, 507.25, 0.80)

Dear All I am dealing at the moment with optimization problems with nonlinear constraints. Regenoud is quite apt to solve that kind of problems, but the precision of the optimal values for the parameters is sometimes far from what I need. Optim seems to be more precise, but it can only accept box-constrained optimization problems. I read in the list archives that optim can also be used with

> > >From: robert-mcfadden w o2.pl > > >Date: 2008/04/02 Wed AM 09:58:28 CDT > > >To: r-help w r-project.org > > >Subject: [R] Nonlinear equation > > > > hi: you need to give an example and details or > > you won't get much response, if any. Equation e.g. (A, B are known constants): 3log(gamma(x))-log(gamma(x)*gamma(2x))+(x-1)*A+B=0

Hi, Given a positive integer N, and a real number \lambda such that 0 < \lambda < 1, I would like to generate an N by N stochastic matrix (a matrix with all the rows summing to 1), such that it has the second largest eigenvalue equal to \lambda (Note: the dominant eigenvalue of a stochastic matrix is 1). I don't care what the other eigenvalues are. The second eigenvalue is

Hello all, I have an optimization routine that is giving me good results, but the results are not in the nice "model" format like "lm". How can I get optim results into a model so that I can use the clever 'fitted', 'residuals', and 'summary' functions? Using optim is the only way that I was able to make a model that 1) sums the betas to 1, 2)

Dear R-Help List, I am using optim, with method=L-BFGS-B, to maximize a likelihood inside a large simulation exercise. This runs fine for most simulated data sets, but for some reason, about 1 out of 100 times, optim will just hang. Using a dumb approach to the problem (i.e. printing the parameter values each time the function being maximized is evaluated), I tracked down when this happens,

Hi, I would like to solve a system of coupled ordinary differential equations, where there is a delay (time lag) term. I would like to use the "lsoda" function "odesolve" package. However, I am not sure how to specify the delay term using the syntax allowed by odesolve. Here is an example of the kind of problem that I am trying to solve: > library(odesolve)