Adaptive Regression for Modeling Nonlinear Relationships

Discover the innovative world of nonlinear relationships in "Adaptive Regression for Modeling Nonlinear Relationships" by George J. Knafl, published by Springer International Publishing AG in 2016. This comprehensive 372-page hardback delves into advanced methods for assessing whether relationships in your data are linear or nonlinear, providing you with the tools to adaptively fit the right models. Knafl expertly compares adaptive modeling techniques with generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes, making this book an essential resource for statisticians, data analysts, and researchers. Enhance your understanding of nonlinear modeling and elevate your analytical skills with this insightful first edition. Perfect for those looking to deepen their expertise in adaptive regression methodologies.