Model Discrimination for Nonlinear Regression Models

Explore the intricate world of statistical modeling with Model Discrimination for Nonlinear Regression Models by Borowiak. Published by Taylor & Francis Inc in 1989, this hardback edition spans 200 pages and offers a comprehensive examination of model discrimination based on incorrect selection probabilities. Borowiak, a mathematics expert from the University of Akron, delves into diagnostic statistics and formal hypothesis testing procedures to evaluate model fit and stability. Additionally, this insightful text explains the application of advanced computer techniques, including the jackknife and bootstrap methods, enhancing your understanding of nonlinear regression models. Perfect for statisticians, researchers, and students alike, this book is an essential addition to your library for mastering complex data analysis.