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Nonlinear multiple regression methods: a survey and extensions

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  • Kenneth O. Cogger
Abstract
This paper reviews some nonlinear statistical procedures useful in function approximation, classification, regression and time‐series analysis. Primary emphasis is on piecewise linear models such as multivariate adaptive regression splines, adaptive logic networks, hinging hyperplanes and their conceptual differences. Potential and actual applications of these methods are cited. Software for implementation is discussed, and practical suggestions are given for improvement. Examples show the relative capabilities of the various methods, including their ability for universal approximation. Copyright © 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • Kenneth O. Cogger, 2010. "Nonlinear multiple regression methods: a survey and extensions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(1), pages 19-39, January.
    • Handle: RePEc:wly:isacfm:v:17:y:2010:i:1:p:19-39
    DOI: 10.1002/isaf.311
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    1. Harvey, Campbell R., 2001. "The specification of conditional expectations," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 573-637, December.
    2. Leora Friedberg, 2000. "The Labor Supply Effects of the Social Security Earnings Test," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 48-63, February.
    3. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    4. Wachsmuth A. & Wilkinson L. & Dallal G.E., 2003. "Galtons Bend: A Previously Undiscovered Nonlinearity in Galtons Family Stature Regression Data," The American Statistician, American Statistical Association, vol. 57, pages 190-192, August.
    5. Kurt M. Fanning & Kenneth O. Cogger, 1994. "A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 3(4), pages 241-252, December.
    6. Morck, Randall & Shleifer, Andrei & Vishny, Robert W., 1988. "Management ownership and market valuation," Scholarly Articles 29407535, Harvard University Department of Economics.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. Cooper, Suzanne J, 1998. "Multiple Regimes in U.S. Output Fluctuations," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 92-100, January.
    9. Jonq-Ying Lee & Mark G. Brown, 1985. "Coupon Redemption and the Demand for Frozen Concentrated Orange Juice: A Switching Regression Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(3), pages 647-653.
    10. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    13. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    14. Merz, Monika, 1999. "Time Series Evidence of Unemployment Flows: The Sample Period Matters," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 324-334, July.
    15. Morck, Randall & Shleifer, Andrei & Vishny, Robert W., 1988. "Management ownership and market valuation : An empirical analysis," Journal of Financial Economics, Elsevier, vol. 20(1-2), pages 293-315, January.
    16. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    17. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    18. Greg M. Allenby & Thomas S. Shively & Sha Yang & Mark J. Garratt, 2004. "A Choice Model for Packaged Goods: Dealing with Discrete Quantities and Quantity Discounts," Marketing Science, INFORMS, vol. 23(1), pages 95-108, June.
    19. Kurt Fanning & Kenneth O. Cogger & Rajendra Srivastava, 1995. "Detection of Management Fraud: A Neural Network Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(2), pages 113-126, June.
    20. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 853-883.
    21. Proietti Tommaso, 1998. "Characterizing Asymmetries in Business Cycles Using Smooth-Transition Structural Time-Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(3), pages 1-18, October.
    22. Ritchken, Peter H, 1985. "On Option Pricing Bounds," Journal of Finance, American Finance Association, vol. 40(4), pages 1219-1233, September.
    23. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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