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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Do not respect bounds when computing gradients or Hessians
Alias: none
Argument(s): none
Default: bounds respected
When Dakota computes gradients or Hessians by finite differences and the variables in question have bounds, it by default chooses finite-differencing steps that keep the variables within their specified bounds. Older versions of Dakota generally ignored bounds when computing finite differences. To restore the older behavior, one can add keyword ignore_bounds
to the response
specification when method_source dakota
(or just dakota
) is also specified.
In forward difference or backward difference computations, honoring bounds is straightforward.
To honor bounds when approximating , i.e., component
of the gradient of
, by central differences, Dakota chooses two steps
and
with
, such that
and
both satisfy the bounds, and then computes
with ,
, and
.