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通过似然基追踪进行变量选择与模型构建AI 解读

This article presents a nonparametric penalized likelihood approach for variable selection and model building, called likelihood basis pursuit (LBP). In the setting of a tensor product reproducing kernel Hilbert space, we decompose the log-likelihood into the sum of different functional components such as main effects and interactions, with each component represented by appropriate basis functions. Basis functions are chosen to be compatible with variable selection and model…

多元伯努利观测的平滑样条方差分析及眼科应用AI 解读

We combine a smoothing spline analysis of variance (SS-ANOVA) model and a log-linear model to build a partly flexible model for multivariate Bernoulli data. The joint distribution conditioning on the predictor variables is estimated. The log odds ratio is used to measure the association between outcome variables. A numerical scheme based on the block one-step successive over relaxation SOR–Newton-Ralphson algorithm is proposed to obtain an approximate solution for the…

大规模伯努利数据的平滑样条 ANOVA 模型与随机化 GACVAI 解读

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…

针对有序备择的多元多样本分位数检验AI 解读

We propose and study a multivariate c-sample rank test for order-restricted alternatives when the underlying distributions have a contaminated component. An example concerning lens opacity in adults is presented. The asymptotic distributions are obtained under local mixture alternatives, and Pitman efficiencies are calculated. An empirical power study is also included.

针对有序备择的多元多样本分位数检验AI 解读

We propose and study a multivariate c-sample rank test for order-restricted alternatives when the underlying distributions have a contaminated component. An example concerning lens opacity in adults is presented. The asymptotic distributions are obtained under local mixture alternatives, and Pitman efficiencies are calculated. An empirical power study is also included.