Model discrimination and criticism with single‐response data

Warren E. Stewart · Thomas L. Henson · George E. P. Box

36 citations0/0 files storedAIChE Journal

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Optimal Experimental Design Methods Control Systems and Identification Statistical Methods and Bayesian Inference

Abstract

Abstract The inverse probability theorem of Bayes is used, along with sampling theory, to obtain objective criteria for choosing among rival models. Formulas are given for the relative posterior probabilities of candidate models and for their goodness of fit, when the models are fitted to a common data set with Normally distributed errors. Cases of full, partial and minimal variance information are treated. The formulas are demonstrated with three examples, including a kinetic study of a catalytic reaction.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 36 citations exist upstream.

References

1951On the Experimental Attainment of Optimum Conditions 1957Multi-Factor Experimental Designs for Exploring Response Surfaces 1959DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS 1954The Exploration and Exploitation of Response Surfaces: Some General Considerations and Examples 1966A Review of Response Surface Methodology: A Literature Survey 1967Discrimination Among Mechanistic Models 1966Selection of Variables for Fitting Equations to Data 1992Parameter estimation from multiresponse data

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.