Premium
Optimal Bayesian Design of Experiments Applied to Nitroxide‐Mediated Radical Polymerization
Author(s) -
Nabifar Afsaneh,
McManus Neil T.,
VivaldoLima Eduardo,
Reilly Park M.,
Penlidis Alexander
Publication year - 2010
Publication title -
macromolecular reaction engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 32
eISSN - 1862-8338
pISSN - 1862-832X
DOI - 10.1002/mren.200900071
Subject(s) - bayesian probability , variety (cybernetics) , computer science , design of experiments , nitroxide mediated radical polymerization , quality (philosophy) , process (computing) , polymerization , materials science , mathematics , radical polymerization , artificial intelligence , statistics , physics , operating system , polymer , quantum mechanics , composite material
Bayesian design of experiments is a powerful method which offers several distinct benefits over standard experimental designs. The basics of the method are briefly described, followed by four case studies giving a step‐by‐step illustration of its application to both bimolecular and unimolecular NMRP. Firstly, the Bayesian design is an improvement with respect to information content retrieved from process data. It allows one to change the levels of factors with relative ease and is flexible and “cost”‐effective with respect to the number of experiments. More importantly, the method has the ability to incorporate into the design prior knowledge coming from a variety of sources. Diagnostic criteria can shed more light on the quality of prior knowledge and the significance of estimated effects.