Dear Florent,
I know that I'm asking to optim to minimize my values, and that the results with a lower fvalue are best supported than those with a higher fvalue. My comment was just from a data point of view. I'd like the lower ms (second parameter) as possible, as well as the fvalue. So a ms of 0.97 (i.e. that 97% of my individuals are coming from outside the experiment plot) is very disapointing.

Dear John,
I can send you my data by email. It's very kind of you to offer to use my data as test for your new and coming optimx ! thank you.

Le 11/30/2011 12:08 PM, Florent D. a écrit :
With     optimx(c(30,50),ms=c(0.4,0.5), fn=LogLiketot)

where

LogLiketot<- function(dist,ms) {
    res<- NULL
    for(i in 1:nrow(pop5)) {
       for(l in 1:nrow(freqvar)) {
          res<- c(res, pop5[i,l]*log(LikeGi(l,i,dist,ms)))
       }
    }
    return(-sum(res))
}

I think it will do something like this for the first call to LogLiketot:

LogLiketot(c(30,50), ms=c(0.4,0.5))

which is obviously not the usage you had in mind.

Also, I see you say the results for the bad usage above:

                    par  fvalues      method fns grs itns conv KKT1 KKT2 xtimes
2    19.27583, 25.37964 2249.698        BFGS  12   8 NULL    0 TRUE TRUE   57.5
1 29.6787861, 0.1580298 2248.972 Nelder-Mead  51  NA NULL    0 TRUE TRUE   66.3
look very good but you do not comment about the results for the
correct usage of optimx:

                    par  fvalues      method fns grs itns conv KKT1 KKT2 xtimes
2 39.9969607, 0.9777634 1064.083        BFGS  29  10 NULL    0 TRUE   NA  92.03
1 39.7372199, 0.9778101 1064.083 Nelder-Mead  53  NA NULL    0 TRUE   NA  70.83
Do you realize optimx is trying to _minimize_ your function? See that
the fvalues from the correct usage are much better (smaller) than you
first (bad) usage.





On Wed, Nov 30, 2011 at 4:16 AM, Diane Bailleul
<diane.baill...@u-psud.fr>  wrote:
Le 11/30/2011 2:09 AM, Florent D. a écrit :

Thanks for your answer !

I also think your last write-up for LogLiketot (using a single
argument "par") is the correct approach if you want to feed it to
optim().
I'm not dedicated to optim() fonction. I just want to optimise my two
parameters and the loglikelihood result, and if there's a better fonction
for that, I wish I could use it.


So now you have a problem with  log(LikeGi(l, i, par[1], par[2])) for
some values of par[1] and par[2].

Where is LikeGi coming from? a package or is it your own function?
My own function, otherwise it would be simplier to discuss about my
problems.


You could add some print statements (if you are familiar with
"browser()" it is even better) so you may see what values of "par" are
causing trouble.
I'm not familiar, but I'll search about browser().

If the function with par is correct, any idea of what I've made with this :

optimx(c(30,50),ms=c(0.4,0.5), fn=LogLiketot)


?




On Tue, Nov 29, 2011 at 1:15 PM, Diane Bailleul
<diane.baill...@u-psud.fr>    wrote:
Good afternoon everybody,
I'm quite new in functions optimization on R and, whereas I've read lot's
of
function descriptions, I'm not sure of the correct settings for function
like "optimx" and "nlminb".
I'd like to minimize my parameters and the loglikelihood result of the
function.
My parameters are a mean distance of dispersion and a proportion of
individuals not assigned, coming from very far away.
The function LikeGi reads external tables and it's working as I want
(I've
got a similar model on Mathematica).

My "final" function is LogLiketot :
LogLiketot<- function(dist,ms)
{
res<- NULL
for(i in 1:nrow(pop5)){
    for(l in 1:nrow(freqvar)){
res<- c(res, pop5[i,l]*log(LikeGi(l,i,dist,ms)))
    }
        }
return(-sum(res))
            }

dist is the mean dispersal distance (0, lots of meters) and ms the
proportion of individuals (0-1).
Of course, I want them to be as low as possible.

I'd tried to enter the initials parameters as indicated in the tutorials
:
optim(c(40,0.5), fn=LogLiketot)
Error in 1 - ms : 'ms' is missing
But ms is 0.5 ...

So I've tried this form :
optimx(c(30,50),ms=c(0.4,0.5), fn=LogLiketot)
with different values for the two parameters :
                    par  fvalues      method fns grs itns conv KKT1 KKT2
xtimes
2    19.27583, 25.37964 2249.698        BFGS  12   8 NULL    0 TRUE TRUE
57.5
1 29.6787861, 0.1580298 2248.972 Nelder-Mead  51  NA NULL    0 TRUE TRUE
66.3
The first line is not possible but as I've not constrained the
optimization
... but the second line would be a very good result !

Then, searching for another similar cases, I've tried to change my
function
form:

LogLiketot<- function(par)
{
res<- NULL
for(i in 1:nrow(pop5)){
    for(l in 1:nrow(freqvar)){
res<- c(res, pop5[i,l]*log(LikeGi(l,i,par[1],par[2])))
    }
        }
return(-sum(res))
            }

where dist=par[1] and ms=par[2]

And I've got :
optimx(c(40,0.5), fn=LogLiketot)
                    par  fvalues      method fns grs itns conv KKT1 KKT2
xtimes
2 39.9969607, 0.9777634 1064.083        BFGS  29  10 NULL    0 TRUE   NA
  92.03
1 39.7372199, 0.9778101 1064.083 Nelder-Mead  53  NA NULL    0 TRUE   NA
  70.83
And I've got now a warning message :
In log(LikeGi(l, i, par[1], par[2])) : NaNs produced
(which are very bad results in that case)


Anyone with previous experiences in optimization of several parameters
could
indicate me the right way to enter the initial parameters in this kind of
functions ?

Thanks a lot for helping me !

Diane

--
Diane Bailleul
Doctorante
Université Paris-Sud 11 - Faculté des Sciences d'Orsay
Unité Ecologie, Systématique et Evolution
Département Biodiversité, Systématique et Evolution
UMR 8079 - UPS CNRS AgroParisTech
Porte 320, premier étage, Bâtiment 360
91405 ORSAY CEDEX FRANCE
(0033) 01.69.15.56.64

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


--
Diane Bailleul
Doctorante
Université Paris-Sud 11 - Faculté des Sciences d'Orsay
Unité Ecologie, Systématique et Evolution
Département Biodiversité, Systématique et Evolution
UMR 8079 - UPS CNRS AgroParisTech
Porte 320, premier étage, Bâtiment 360
91405 ORSAY CEDEX FRANCE
(0033) 01.69.15.56.64




--
Diane Bailleul
Doctorante
Université Paris-Sud 11 - Faculté des Sciences d'Orsay
Unité Ecologie, Systématique et Evolution
Département Biodiversité, Systématique et Evolution
UMR 8079 - UPS CNRS AgroParisTech
Porte 320, premier étage, Bâtiment 360
91405 ORSAY CEDEX FRANCE
(0033) 01.69.15.56.64

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

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