nlminb with constraints failing on some platforms
I'm not entirely sure what you are asking. However, optimx is really NOT meant as a production tool. I intend it as a way to 1) try out a lot of optimizers quickly on a user's problem or problem class to select a method or methods that suit well; 2) to provide (in the source code of optimr()) an example of how to call the particular optimizers. They all have a lot of different syntax elements, which in fact are the biggest headache in building and extending optimx. Best, JN
On 2019-01-31 9:26 a.m., Amit Mittal wrote:
Prof Nash, Prof Galanos Is it possible to use a generic code stub in front of packages that use optimx to improve optimx use or curtail it according to the requirements? Best Regards Amit +91 7899381263 ? ? ? ? ? ?________________________________________________________________________ Please request Skype as available? 5^th ?Year FPM (Ph.D.) in Finance and Accounting Area Indian Institute of Management, Lucknow, (U.P.) 226013 India http://bit.ly/2A2PhD AEA Job profile :?http://bit.ly/AEAamit FMA 2 page profile :?http://bit.ly/FMApdf2p SSRN top10% downloaded since July 2017:?http://ssrn.com/author=2665511
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On Thu, Jan 31, 2019 at 7:22 PM ProfJCNash <profjcnash at gmail.com
<mailto:profjcnash at gmail.com>> wrote:
This is not about the failure on some platforms, which is an important
issue. However, what is below may provide a temporary workaround until
the source of the problem is uncovered.
FWIW, the problem seems fairly straightforward for most optimizers at my
disposal in the R-forge (developmental) version of the optimx package at
https://r-forge.r-project.org/projects/optimizer/
I used the code
## KKristensen19nlminb.R
f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 )
opt <- nlminb(rep(0, 10), f, lower=-1, upper=3)
xhat <- rep(1, 10)
abs( opt$objective - f(xhat) ) < 1e-4? ## Must be TRUE
opt
library(optimx)
optx <- opm(rep(0,10), f, lower=-1, upper=3, method="ALL")
summary(optx, order=value)
optxc <- opm(rep(0,10), f, gr="grcentral", lower=-1, upper=3,
method="ALL")
summary(optxc, order=value)
optxn <- opm(rep(0,10), f, gr="grnd", lower=-1, upper=3, method="ALL")
summary(optxn, order=value)
It should not be too difficult to actually supply the gradient, which
would give speedier and more reliable outcomes.
JN
On 2019-01-28 3:56 a.m., Kasper Kristensen via R-devel wrote:
> I've noticed unstable behavior of nlminb on some Linux systems.
The problem can be reproduced by compiling R-3.5.2 using gcc-8.2 and
running the following snippet:
>
> f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 )
> opt <- nlminb(rep(0, 10), f, lower=-1, upper=3)
> xhat <- rep(1, 10)
> abs( opt$objective - f(xhat) ) < 1e-4? ## Must be TRUE
>
> The example works perfectly when removing the bounds. However,
when bounds are added the snippet returns 'FALSE'.
>
> An older R version (3.4.4), compiled using the same gcc-8.2, did
not have the problem. Between the two versions R has changed the
flags to compile Fortran sources:
>
> < SAFE_FFLAGS = -O2 -fomit-frame-pointer -ffloat-store
> ---
>> SAFE_FFLAGS = -O2 -fomit-frame-pointer -msse2 -mfpmath=sse
>
> Reverting to the old SAFE_FFLAGS 'solves' the problem.
>
>> sessionInfo()
> R version 3.5.2 (2018-12-20)
> Platform: x86_64-pc-linux-gnu (64-bit)
> Running under: Scientific Linux release 6.4 (Carbon)
>
> Matrix products: default
> BLAS/LAPACK:
/zdata/groups/nfsopt/intel/2018update3/compilers_and_libraries_2018.3.222/linux/mkl/lib/intel64_lin/libmkl_gf_lp64.so
>
> locale:
> [1] C
>
> attached base packages:
> [1] stats? ? ?graphics? grDevices utils? ? ?datasets? methods? ?base
>
> loaded via a namespace (and not attached):
> [1] compiler_3.5.2
>
>
>
>? ? ? ?[[alternative HTML version deleted]]
>
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