Premium
Deterministic and Stochastic Parameter Estimation for Polymer Reaction Kinetics I: Theory and Simple Examples
Author(s) -
Wulkow Niklas,
Telgmann Regina,
Hungenberg KlausDieter,
Schütte Christof,
Wulkow Michael
Publication year - 2021
Publication title -
macromolecular theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 56
eISSN - 1521-3919
pISSN - 1022-1344
DOI - 10.1002/mats.202170012
Subject(s) - simple (philosophy) , cover (algebra) , connection (principal bundle) , estimation theory , statistical physics , mathematics , computer science , bayesian probability , bayes' theorem , polymerization , mathematical optimization , polymer , materials science , algorithm , physics , artificial intelligence , engineering , mechanical engineering , philosophy , geometry , epistemology , composite material
Front Cover : In article number 2100017, Michael Wulkow and co‐workers refine and apply classical and Bayesian parameter estimation for polymerization. This article aims at showing the mathematical connection of both approaches and how their combination can and should be leveraged in a closed workflow to derive a strong understanding of a model and its parameters.