Diagnostics for penalized least-squares estimators |
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| Affiliation: | 1. Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Collaborative Innovation of Modern Crops and Food Crops in Jiangsu/Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou 225009, Jiangsu, China;2. USDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS 66506, USA;3. Agriculture & Agrifood Canada, Ottawa Research & Development Centre, Ottawa, ON K1A 0C6, Canada;1. Aerospace Research Institute of Materials and Processing Technology, Beijing, 100076, China;2. Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China;3. Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Beijing, 100084, China;4. Shanghai Key Laboratory of Digital Manufacture of Thin-walled Structures, Shanghai, 200240, China |
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| Abstract: | Diagnostic methods for a class of penalized least-squares estimators are derived from a Bayesian perspective. The class of estimators considered includes generalized ridge estimators, partial splines and thin plate smoothing splines. The proposed diagnostics include scaled residuals, leverage values and various measures of influence. |
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