Your function is very irregular, so the optim is likely to return
local minima rather than global minima.
Try different methods (SANN, CG, BFGS) and see if you get the result
you need. As with all numerical optimsation, I would check the
sensitivity of the results to starting values.
Nikhil Kaza
Asst. Professor,
City and Regional Planning
University of North Carolina
nikhil.l...@gmail.com
On Jun 26, 2010, at 4:27 PM, Derek Ogle wrote:
I am trying to use optim() to minimize a sum-of-squared deviations
function based upon four parameters. The basic function is defined
as ...
SPsse <- function(par,B,CPE,SSE.only=TRUE) {
n <- length(B) # get number of years of
data
B0 <- par["B0"] # isolate B0 parameter
K <- par["K"] # isolate K parameter
q <- par["q"] # isolate q parameter
r <- par["r"] # isolate r parameter
predB <- numeric(n)
predB[1] <- B0
for (i in 2:n) predB[i] <- predB[i-1]+r*predB[i-1]*(1-predB[i-1]/K)-
B[i-1]
predCPE <- q*predB
sse <- sum((CPE-predCPE)^2)
if (SSE.only) sse
else list(sse=sse,predB=predB,predCPE=predCPE)
}
My call to optim() looks like this
# the data
d <- data.frame(catch=
c
(90000,113300,155860,181128,198584,198395,139040,109969,71896,59314,62300,65343,76990,88606,118016,108250,108674
),
cpe
=
c
(109.1,112.4,110.5,99.1,84.5,95.7,74.1,70.2,63.1,66.4,60.5,89.9,117.0,93.0,116.6,90.0,105.1
))
pars <- c(800000,1000000,0.0001,0.17) # put all
parameters into one vector
names(pars) <- c("B0","K","q","r") # name the
parameters
( SPoptim <- optim(pars,SPsse,B=d$catch,CPE=d$cpe) ) # run optim()
This produces parameter estimates, however, that are not at the
minimum value of the SPsse function. For example, these parameter
estimates produce a smaller SPsse,
parsbox <- c(732506,1160771,0.0001484,0.4049)
names(parsbox) <- c("B0","K","q","r")
( res2 <- SPsse(parsbox,d$catch,d$cpe,SSE.only=FALSE) )
Setting the starting values near the parameters shown in parsbox
even resulted in a movement away from (to a larger SSE) those
parameter values.
( SPoptim2 <- optim(parsbox,SPsse,B=d$catch,CPE=d$cpe) ) # run
optim()
This "issue" most likely has to do with my lack of understanding of
optimization routines but I'm thinking that it may have to do with
the optimization method used, tolerance levels in the optim
algorithm, or the shape of the surface being minimized.
Ultimately I was hoping to provide an alternative method to
fisheries biologists who use Excel's solver routine.
If anyone can offer any help or insight into my problem here I would
be greatly appreciative. Thank you in advance.
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
