I have to make correction in my error message which I introduced in my
original message. Sorry for my mistake.
Finally, I had the following error message after running the function '
genoud'.
Error in optim(foo.vals, fn = fn1, gr = gr1, method = optim.method, control
= control) :
non-finite finite-difference value [1]
When I execute 'traceback()' to trace where the error occured, I got the
following results. Unfortunately, I could not figure out what was the
problem from the above information.
6: optim(foo.vals, fn = fn1, gr = gr1, method = optim.method, control =
control)
5: function (foo.vals)
{
ret <- optim(foo.vals, fn = fn1, gr = gr1, method = optim.method,
control = control)
return(c(ret$value, ret$par))
}(c(0.220878697173384, -13.3643173824871))
4: .Call("rgenoud", as.function(fn1), new.env(), as.integer(nvars),
as.integer(pop.size), as.integer(max.generations),
as.integer(wait.generations),
as.integer(nStartingValues), as.real(starting.values), as.vector(P),
as.matrix(Domains), as.integer(max), as.integer(gradient.check),
as.integer(boundary.enforcement), as.double(solution.tolerance),
as.integer(BFGS), as.integer(data.type.int),
as.integer(provide.seeds),
as.integer(unif.seed), as.integer(int.seed),
as.integer(print.level),
as.integer(share.type), as.integer(instance.number),
as.integer(MemoryMatrix),
as.integer(debug), as.character(output.path),
as.integer(output.type),
as.character(project.path), as.integer(hard.generation.limit),
as.function(genoud.optim.wrapper101), as.integer(lexical),
as.function(fnLexicalSort), as.function(fnMemoryMatrixEvaluate),
as.integer(UserGradient), as.function(gr1func), as.real(P9mix),
as.integer(BFGSburnin), as.integer(transform), PACKAGE = "rgenoud")
3: genoud(Qmin, nvars = 2, starting.values = InitVal, max.generations = 10,
wait.generations = 3, n = n, yper = yper, pertype = pertype) at
wFGN.R#75
On 13 October 2010 13:03, Wonsang You <y...@ifn-magdeburg.de> wrote:
> Dear R user fellows,
>
> I would like to ask you about the package 'rgenoud' which is a genetic
> optimization tool.
> I ran the function 'genoud' with two variables to be minimized by the
> following command.
>
> result<-genoud(fn,nvars=2,starting.values=c(0.5,0),
>
> pop.size=1000, max.generations=10, wait.generations=3)
>
>
> Then, I had the following error message.
>
> Error in solve.default(Djl) :
>
> system is computationally singular: reciprocal condition number = 0
>
>
> Can anyone give me some tip on how to fix the problem? Thank you for your
> great help in advance.
>
> Best Regards,
> Wonsang You
>
-----
Wonsang You
Leibniz Institute for Neurobiology
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