Sequential Sampling to Myopically Maximize the Expected Value of Information

• Published in: INFORMS journal on computing Vol. 22; no. 1; pp. 71 - 80
• Main Authors: Chick, Stephen E, Branke, Jurgen, Schmidt, Christian
• Format: Journal Article
• Language: English
• Published: Linthicum INFORMS 01.01.2010; Institute for Operations Research and the Management Sciences
• Subjects: Algorithms; Approximation; Approximation theory; Asymptotic methods; Bayesian; Bayesian analysis; Bayesian statistical decision theory; decision analysis; Expected values; Information management; Methods; Sampling; sequential; simulation; statistical analysis; Statistical sampling; statistics; Studies; United States

Statistical selection procedures are used to select the best of a finite set of alternatives, where "best" is defined in terms of each alternative's unknown expected value, and the expected values are inferred through statistical sampling. One effective approach, which is based on a B...