Nonlinear regression modeling via regularized wavelets and smoothing parameter selection

Toru Fujii and Sadanori Konishi

Journal of Multivariate Analysis, 2006, vol. 97, issue 9, 2023-2033

Abstract: We introduce regularized wavelet-based methods for nonlinear regression modeling when design points are not equally spaced. A crucial issue in the model building process is a choice of tuning parameters that control the smoothness of a fitted curve. We derive model selection criteria from an information-theoretic and also Bayesian approaches. Monte Carlo simulations are conducted to examine the performance of the proposed wavelet-based modeling technique.

Keywords: Automatic; smoothing; parameter; selection; Irregular; design; points; Linear; shrinkage; Regression; modeling; Wavelets (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (1)

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