# [R] Dealing with -Inf in a maximisation problem.

William Dunlap wdunlap at tibco.com
Mon Nov 7 01:07:43 CET 2016

```Have you tried reparameterizing, using logb (=log(b)) instead of b?

Bill Dunlap
TIBCO Software
wdunlap tibco.com

On Sun, Nov 6, 2016 at 1:17 PM, Rolf Turner <r.turner at auckland.ac.nz> wrote:

>
> I am trying to deal with a maximisation problem in which it is possible
> for the objective function to (quite legitimately) return the value -Inf,
> which causes the numerical optimisers that I have tried to fall over.
>
> The -Inf values arise from expressions of the form "a * log(b)", with b =
> 0.  Under the *starting* values of the parameters, a must equal equal 0
> whenever b = 0, so we can legitimately say that a * log(b) = 0 in these
> circumstances.  However as the maximisation algorithm searches over
> parameters it is possible for b to take the value 0 for values of
> a that are strictly positive.  (The values of "a" do not change during
> this search, although they *do* change between "successive searches".)
>
> Clearly if one is *maximising* the objective then -Inf is not a value of
> particular interest, and we should be able to "move away".  But the
> optimising function just stops.
>
> It is also clear that "moving away" is not a simple task; you can't
> estimate a gradient or Hessian at a point where the function value is -Inf.
>
> Can anyone suggest a way out of this dilemma, perhaps an optimiser that is
> equipped to cope with -Inf values in some sneaky way?
>
> Various ad hoc kludges spring to mind, but they all seem to be fraught
> with peril.
>
> I have tried changing the value returned by the objective function from
> "v" to exp(v) --- which maps -Inf to 0, which is nice and finite. However
> this seemed to flatten out the objective surface too much, and the search
> stalled at the 0 value, which is the antithesis of optimal.
>
> The problem arises in a context of applying the EM algorithm where the
> M-step cannot be carried out explicitly, whence numerical optimisation.
> I can give more detail if anyone thinks that it could be relevant.
>
>
> cheers,
>
> Rolf Turner
>
> --
> Technical Editor ANZJS
> Department of Statistics
> University of Auckland
> Phone: +64-9-373-7599 ext. 88276
>
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