The function needs to have a single parameter. Then extract each
parameter.
For example, or see first example in help for optim.
errorFunction <- function(params) {
localShifts <- params[1]
etc
>>> "Gerster Sarah" <[EMAIL PROTECTED]> 01/03/07 9:22 PM >>>
Hi!
I'm trying to figure out how to use optim... I get some really strange
results, so I guess I got something wrong.
I defined the following function which should be minimized:
errorFunction <-
function(localShifts,globalShift,fileName,experimentalPI,lambda)
{
lambda <- 1/sqrt(147)
# error <- abs(errHuber(localShifts,globalShift,
#
"/home/sarah/Semesterarbeit/Sequences/R/R1593_filtered.data",3.48)) +
# sum(abs(localShifts))*lambda
error <- sum(abs(localShifts))*lambda
error # return the error to be minimized
}
Then I call optim:
par <- seq(length=9, from=0, by=0)
lambda <- 1/sqrt(147)
optim(par, errorFunction, gr=NULL, method="Nelder-Mead", hessian=FALSE,
globalShift,
"/home/sarah/Semesterarbeit/Sequences/R/R1593_filtered.data",
experimentalPI=3.48, lambda = lambda)
The output is:
$par
[1] 0.56350964 0.56350964 0.56350964 0.56350964 0.00000000
-0.29515957
[7] 0.00569937 0.32543297 0.18615880
$value
[1] 0.2529198
$counts
function gradient
31 31
$convergence
[1] 0
$message
[1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH"
Warning messages:
1: bounds can only be used with method L-BFGS-B in: optim(par,
errorFunction, gr = NULL, method = "Nelder-Mead",
2: NAs introduced by coercion
If I change my "error-function" to
errorFunction <-
function(localShifts,globalShift,fileName,experimentalPI,lambda)
{
error <- sum(abs(localShifts*lambda))
error # return the error to be minimized
}
or to:
errorFunction <-
function(localShifts,globalShift,fileName,experimentalPI,lambda)
{
error <- sum(abs(localShifts))/sqrt(147)
error # return the error to be minimized
}
The output is:
$par
[1] 6.018101e-20 6.018101e-20 6.018101e-20 6.018101e-20
0.000000e+00
[6] 5.176245e-21 -4.002183e-21 -8.254019e-20 3.231412e-21
$value
[1] 2.768593e-20
$counts
function gradient
76 76
$convergence
[1] 0
$message
[1] "CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL"
Warning messages:
1: bounds can only be used with method L-BFGS-B in: optim(par,
errorFunction, gr = NULL, method = "Nelder-Mead",
2: NAs introduced by coercion
- What is wrong with the first version?
Thanks for the help!
Sarah
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and provide commented, minimal, self-contained, reproducible code.
