scholarly journals Discussion: “Bayesian Optimal Design of Experiments for Inferring the Statistical Expectation of Expensive Black-Box Functions” (Pandita, P., Bilionis, I., and Panchal, J., 2019. ASME. J. Mech. Des. 141(10): 101404)

2021 ◽  
pp. 1-5
Author(s):  
Xianliang Gong ◽  
Yulin Pan
Keyword(s):  
Optimal Design ◽  
Design Of Experiments ◽  
Black Box ◽  
Optimal Design Of Experiments ◽  
Analytical Computation ◽  
Input Distribution ◽  
Bayesian Optimal Design ◽  
Statistical Expectation ◽  
Intuitive Interpretation

Abstract The authors of the discussed paper simplified the information-based acquisition on estimating statistical expectation and developed analytical computation for each involved quantity under uniform input distribution. In this discussion, we show that (1) the last three terms of the acquisition always add up to zero, leaving a concise form with a much more intuitive interpretation of the acquisition; (2) the analytical computation of the acquisition can be generalized to arbitrary input distribution, greatly broadening the application of the developed framework.

Bayesian Optimal Design of Experiments for Inferring the Statistical Expectation of Expensive Black-Box Functions

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Piyush Pandita ◽  
Ilias Bilionis ◽  
Jitesh Panchal
Keyword(s):  
Optimal Design ◽  
Design Of Experiments ◽  
Information Gain ◽  
Black Box ◽  
Expected Information ◽  
Bayesian Optimal Design ◽  
Physical Response ◽  
Hypothetical Experiment ◽  
Statistical Expectation ◽  
Expected Information Gain

Abstract Bayesian optimal design of experiments (BODEs) have been successful in acquiring information about a quantity of interest (QoI) which depends on a black-box function. BODE is characterized by sequentially querying the function at specific designs selected by an infill-sampling criterion. However, most current BODE methods operate in specific contexts like optimization, or learning a universal representation of the black-box function. The objective of this paper is to design a BODE for estimating the statistical expectation of a physical response surface. This QoI is omnipresent in uncertainty propagation and design under uncertainty problems. Our hypothesis is that an optimal BODE should be maximizing the expected information gain in the QoI. We represent the information gain from a hypothetical experiment as the Kullback–Liebler (KL) divergence between the prior and the posterior probability distributions of the QoI. The prior distribution of the QoI is conditioned on the observed data, and the posterior distribution of the QoI is conditioned on the observed data and a hypothetical experiment. The main contribution of this paper is the derivation of a semi-analytic mathematical formula for the expected information gain about the statistical expectation of a physical response. The developed BODE is validated on synthetic functions with varying number of input-dimensions. We demonstrate the performance of the methodology on a steel wire manufacturing problem.

scholarly journals Maximal Power Tests for Detecting Defects in Meiotic Recombination

Genetics ◽  
2002 ◽  
Vol 161 (3) ◽  
pp. 1333-1337
Author(s):  
Thomas I Milac ◽  
Frederick R Adler ◽  
Gerald R Smith
Keyword(s):  
Optimal Design ◽  
Design Of Experiments ◽  
Meiotic Recombination ◽  
Region Of Interest ◽  
Genetic Distances ◽  
Genomic Region ◽  
Maximal Power ◽  
Optimal Design Of Experiments ◽  
Crossover Interference ◽  
Single Interval

Abstract We have determined the marker separations (genetic distances) that maximize the probability, or power, of detecting meiotic recombination deficiency when only a limited number of meiotic progeny can be assayed. We find that the optimal marker separation is as large as 30–100 cM in many cases. Provided the appropriate marker separation is used, small reductions in recombination potential (as little as 50%) can be detected by assaying a single interval in as few as 100 progeny. If recombination is uniformly altered across the genomic region of interest, the same sensitivity can be obtained by assaying multiple independent intervals in correspondingly fewer progeny. A reduction or abolition of crossover interference, with or without a reduction of recombination proficiency, can be detected with similar sensitivity. We present a set of graphs that display the optimal marker separation and the number of meiotic progeny that must be assayed to detect a given recombination deficiency in the presence of various levels of crossover interference. These results will aid the optimal design of experiments to detect meiotic recombination deficiency in any organism.

A New Practical Route to ZSM-5 Nanoparticles and Optimization of Synthetic Parameters through D-optimal Design of Experiments

2015 ◽  
Vol 62 (9) ◽  
pp. 817-825 ◽  
Author(s):  
Saeed Soltanali ◽  
Rouein Halladj ◽  
Alimorad Rashidi ◽  
Mansour Bazmi ◽  
Saeed Khodabakhshi
Keyword(s):  
Optimal Design ◽  
Design Of Experiments ◽  
Optimal Design Of Experiments

Optimal design of experiments for estimating the time of death in forensic medicine

2018 ◽  
Vol 34 (12) ◽  
pp. 125005 ◽  
Author(s):  
Martin Weiser ◽  
Yvonne Freytag ◽  
Bodo Erdmann ◽  
Michael Hubig ◽  
Gita Mall
Keyword(s):  
Optimal Design ◽  
Design Of Experiments ◽  
Forensic Medicine ◽  
Time Of Death ◽  
Optimal Design Of Experiments
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