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 xtimes2 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 66.3look 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 xtimes2 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 70.83Do 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 missingBut 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 xtimes2 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 66.3The 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 xtimes2 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 70.83And 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.
