The optim help page mentions scaling in the discussion of the "control"
argument. Specifically under the parscale description:
"Optimization is performed on par/parscale and these should be
comparable in the sense that a unit change in any element produces about
a unit change in the scaled value."
In your function a unit change in x[1] makes a change of 1e-317 in the
function value, and changing x[2] has no effect at all.
It would be nice if violating the rule only led to inefficiencies or
poor stopping decisions, but the numbers you are working with are close
to the hardware limits (the smallest positive number with full precision
is .Machine$double.xmin, about 2e-308), and sometimes that means
assumptions in the code about how arithmetic works are violated, e.g.
things like x*1.1 > x may not be true for positive x below
.Machine$double.xmin .
Duncan Murdoch
On 23/12/2022 12:30 p.m., Collin Erickson wrote:
Hello,
I've come across what seems to be a bug in optim that has become a
for me.
To recreate the bug, run:
optim(c(0,0), function(x) {x[1]*1e-317}, lower=c(-1,-1), upper=c(1,1),
method='L-BFGS-B')
The error message says:
Error in optim(c(0, 0), function(x) { :
non-finite value supplied by optim
What makes this particularly treacherous is that this error only occurs
specific powers. By running the following code you will find that the
only occurs when the power is between -309 and -320; above and below that
work fine.
p <- 1:1000
giveserror <- rep(NA, length(p))
for (i in seq_along(p)) {
tryout <- try({
optim(c(0,0), function(x) {x[1]*10^-p[i]}, lower=c(-1,-1),
upper=c(1,1), method='L-BFGS-B')
})
giveserror[i] <- inherits(tryout, "try-error")
}
p[giveserror]
Obviously my function is much more complex than this and usually doesn't
fail, but this reprex demonstrates that this is a problem. To avoid the
error I may multiply by a factor or take the log, but it seems like a
legitimate bug that should be fixed.
I tried to look inside of optim to track down the error, but the error
within the external C code:
.External2(C_optim, par, fn1, gr1, method, con, lower,
upper)
For reference, I am running R 4.2.2, but was also able to recreate this
on another device running R 4.1.2 and another running 4.0.3.
Thanks,
Collin Erickson
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