Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV
大规模伯努利数据的平滑样条 ANOVA 模型与随机化 GACV
We propose the randomized Generalized Approximate Cross Validation (ranGACV) method for choosing multiple smoothing parameters in penalized likelihood estimates for Bernoulli data. The method is intended for application with penalized likelihood smoothing spline ANOVA models. In addition we propose a class of approximate numerical methods for solving the penalized likelihood variational problem which, in conjunction with the ranGACV method allows the application of smoothing…