High-dimensional analysis of variance in multivariate linear regression
نویسندگان
چکیده
Summary In this paper, we develop a systematic theory for high-dimensional analysis of variance in multivariate linear regression, where the dimension and number coefficients can both grow with sample size. We propose new U-type statistic to test hypotheses establish Gaussian approximation result under fairly mild moment assumptions. Our general framework be used deal classical one-way variance, nonparametric high dimensions. To implement procedure, introduce sample-splitting-based estimator second error covariance discuss its properties. A simulation study shows that our proposed outperforms some existing tests various settings.
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ژورنال
عنوان ژورنال: Biometrika
سال: 2023
ISSN: ['0006-3444', '1464-3510']
DOI: https://doi.org/10.1093/biomet/asad001