Dakota Reference Manual  Version 6.15
Explore and Predict with Confidence
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chain_diagnostics


Compute diagnostic metrics for Markov chain

Specification

Alias: none

Argument(s): none

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Optional confidence_intervals

Calculate the confidence intervals on estimates of first and second moments

Description

While a Markov chain produced via Monte Carlo sampling eventually converges to a set of samples representative of an underlying probability distribution, the first set of samples may not accurately capture the target distribution. Chain diagnostic metrics provide measures of this convergence, and are intended to help users decide whether samples should be increased in Bayesian calibration exercises.