Advanced Regression and Alternatives

Linear regression models are not the only curve-fitting methods in wide use. Also, these methods are not useful for analyzing data for categorical responses. In this chapter, so-called “kriging” models, “artificial neural nets” (ANNs), and logistic regression methods are briefly described. ANNs and logistic regression methods are relevant for categorical responses. Each of the modeling methods described here offers advantages in specific contexts. However, all of these alternatives have a practical disadvantage in that formal optimization must be used in their fitting process.

[1]  M. Ben-Akiva,et al.  Discrete choice analysis , 1989 .

[2]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[3]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[4]  Adrien-Marie Legendre,et al.  Nouvelles méthodes pour la détermination des orbites des comètes , 1970 .

[5]  G. Matheron Principles of geostatistics , 1963 .

[6]  Theodore T. Allen,et al.  Constructing Meta-Models for Computer Experiments , 2003 .

[7]  James C. Bean,et al.  A Genetic Algorithm for the Multiple-Choice Integer Program , 1997, Oper. Res..

[8]  Mark Andrew Chambers Queuing network construction using artificial neural networks , 2000 .

[9]  Thomas J. Santner,et al.  The Design and Analysis of Computer Experiments , 2003, Springer Series in Statistics.

[10]  Charles Louis Ribardo Desirability functions for comparing arc welding parameter optimization methods and for addressing process variability under six sigma assumptions , 2000 .

[11]  M. Wedel,et al.  Designing Conjoint Choice Experiments Using Managers' Prior Beliefs , 2001 .

[12]  D. Hosmer,et al.  Applied Logistic Regression , 1991 .

[13]  Henry P. Wynn,et al.  Screening, predicting, and computer experiments , 1992 .

[14]  W. Welch A mean squared error criterion for the design of experiments , 1983 .

[15]  M. D. McKay,et al.  A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .

[16]  William H. Woodall,et al.  Announcements from the Editor , 2003 .