The information detection for the Generalized Additive Model

• Main Authors: San-Teng Huang, 黃三騰
• Other Authors: Wei-Ying Wu
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/te66eq

碩士 === 國立東華大學 === 應用數學系 === 107 === The regression model consisting of many unknown group regressor functions is assumed in our work, and some of them can be irrelevant for the response variable. To find an appropriate model for the prediction problem and model interpretation, an algorithm is developed to search the important regressor functions and their related structures through the introduction of basis functions with the Lasso-type penalty. The performance of the proposed algorithm is evaluated under simulation studies and real data analyses.