pre_solve

Perform deterministic optimization for MAP before Bayesian calibration

Specification

  • Alias: None

  • Arguments: None

  • Default: nip pre-solve for emulators

Child Keywords:

Required/Optional

Description of Group

Dakota Keyword

Dakota Keyword Description

Required (Choose One)

Pre-solve Optimizer

sqp

Use a sequential quadratic programming method for solving an optimization sub-problem

nip

Use a nonlinear interior point method for solving an optimization sub-problem

none

Deactivates MAP pre-solve prior to initiating the MCMC process.

Description

When specified, Dakota will perform a deterministic derivative-based optimization to maximize the log posterior (minimize the negative log posterior = misfit - log_prior + constant normalization factors). The Markov chain in Bayesian calibration will subsequently be started at the best point found in the optimization (the MAP point), which can eliminate the need for “burn in” of the chain in which some initial portion of the chain is discarded.

Examples

method
  bayes_calibration queso
    samples = 2000 seed = 348
    delayed_rejection
    emulator
      pce sparse_grid_level = 2
      pre_solve nip # default for emulators