Sharpening P-spline signal regression
Document Type
Article
Publication Date
12-1-2008
Abstract
We propose two variations of P-spline signal regression: space-varying penalization signal regression (SPSR) and additive polynomial signal regression (APSR). SPSR uses space-varying roughness penalty according to the estimated coefficients from the partial least-squares (PLS) regression, while APSR expands the linear basis to polynomial bases. SPSR and APSR are motivated in the following two scenarios, respectively: (i) some region(s) of the regressor channels contain more useful information for prediction than others and (ii) the relationship between the response and regressor channels is highly nonlinear. We also extend the methods to the generalized linear regression setting. As illustration, we apply the methods to two published data sets showing highly competitive performance. © 2008 SAGE Publications.
Publication Source (Journal or Book title)
Statistical Modelling
First Page
367
Last Page
383
Recommended Citation
Li, B., & Marx, B. (2008). Sharpening P-spline signal regression. Statistical Modelling, 8 (4), 367-383. https://doi.org/10.1177/1471082X0800800403