固定和自适应设计下高维广义线性模型的经验似然检验

Empirical likelihood test for high-dimensional generalized linear models with fixed and adaptive designs

利用经验似然方法,讨论固定设计和自适应设计下高维广义线性模型中的参数检验问题。数值计算结果表明,所构造的经验对数似然比统计量渐近于标准卡方分布,具有较稳定的真实检验水平和功效。

An empirical likelihood method is considered to test the coefficients in a high-dimensional generalized linear model with fixed and adaptive designs. Numerical analysis show that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution, and the proposed empirical likelihood test has a very stable size with respect to the number of covariates and is powerful too.