协变量
数学
维数(图论)
无穷
无效假设
投影(关系代数)
逻辑回归
空分布
渐近分布
降维
统计假设检验
统计
足够的尺寸缩减
应用数学
计量经济学
计算机科学
回归
算法
估计员
人工智能
检验统计量
组合数学
数学分析
作者
Xinmin Li,Feifei Chen,Hua Liang,David Ruppert
标识
DOI:10.1080/10618600.2022.2084403
摘要
We propose a projection-based test to check logistic regression models when the dimension of the covariate vector may be divergent. The proposed test achieves a reduction in dimension, and the proposed method behaves as if only a single covariate is present. The test is shown to be consistent and can detect root-n local alternatives. We derive the asymptotic distribution of the proposed test under the null hypothesis and establish the test's asymptotic behavior under the local and global alternatives. The numerical performance is remarkably attractive comparing to the existing methods. Real examples are presented for illustration. Supplementary materials for this article are available online.
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