Computer-Aided Modeling of
Warren E. Stewart, Sc.D. and
Michael Caracotsios, Ph.D.
Chemical Reaction Models
Chemical Reactor Models
Introduction to Probability and Statistics
Introduction to Bayesian
Process Modeling with Single-Response Data
Process Modeling with Multi-Response Data
Solution of Linear Algebraic
Appendix B: DDAPLUS Documentation
Appendix C: GREGPLUS Documentation
Scientific learning is an iterative
process that employs experimentation, mathematical modeling, model
criticism and discrimination, as well as nonlinear parameter
estimation and optimization. The mathematical modeling task
encapsulates our knowledge in a well defined set of user postulated
functions. Model criticism induces enhancement and further
modification. Estimation is applied to estimate adjustable
parameters and their posterior probability density conditional on
the model's truth.
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