Statistics and Its Interface
Volume 16 (2023)
On the optimal configuration of a square array group testing algorithm
Pages: 579 – 591
Up to date, only lower and upper bounds for the optimal configuration of a Square Array (A2) Group Testing (GT) algorithm are known. We establish exact analytical formulae and provide a couple of applications of our result. First, we compare the A2 GT scheme to several other classical GT schemes in terms of the gain per specimen attained at optimal configuration. Second, operating under objective Bayesian framework with the loss designed to attain minimum at optimal configuration, we suggest the preferred choice of the group size under natural minimal assumptions: the prior information regarding the prevalence suggests that grouping and application of A2 is better than individual testing. The same suggestion is provided for the Minimax strategy.
group testing, square array, optimal configuration
2010 Mathematics Subject Classification
Primary 62P10, 62-xx. Secondary 92C50, 92-xx.
Received 14 November 2021
Accepted 22 June 2022
Published 14 April 2023