Dale S. Borowiak

Model Discrimination for Nonlinear Regression Models (eBook, PDF)

• Format: PDF

Produktbeschreibung

Borowiak (math, U. of Akron) discusses model discrimination based upon incorrect selection probability, presents diagnostic statistics and formal hypothesis test procedures to assess a model's fit and stability, explains the use of computer computations such as the jackknife and bootstrap, and demonstrates model discrimination techniques through examples taken from real experimental settings. Offering practical guidance that experimenters and students can apply to their own research problems, this definitive reference text is essential reading for statisticians, mathematicians, data analysts, forecasters, applied engineers and advanced undergraduate and graduate students in the above disciplines.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 200
• Erscheinungstermin: 25. November 2020
• Englisch
• ISBN-13: 9781000104127
• Artikelnr.: 60575936

Autorenporträt

Dale S. Borowiak is Associate Professor in the Department of Mathematical Sciences at the University of Akron, Ohio. He has published numerous articles and book reviews in leading statistics journals, and presented professional papers to conferences throughout the U.S. on model development and model discrimination procedures. Dr. Borowiak is a member of the American Statistical Association, Institute of Mathematical Statistics, and Pi Mu Epsilon. He received the B.S. degree (1974) in mathematics and M.S. degree (1976) in statistics from the University of Akron, and Ph.D. degree (1980) in statistics from Bowling Green State University, Bowling Green, Ohio.

Inhaltsangabe

Preface
1. Introduction
2. Completely Determined Models
3. Data-Fitted Models
4. Computer Evaluations
References
Index