A Regularization-Based Adaptive Test for High-Dimensional Generalized Linear Models

In spite of its urgent importance in the era of big data, testing high-dimensional parameters in generalized linear models (GLMs) in the presence of high-dimensional nuisance parameters has been largely under-studied, especially with regard to constructing powerful tests for general (and unknown) al...

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Detalles Bibliográficos
Autores principales: Wu, Chong, Xu, Gongjun, Shen, Xiaotong, Pan, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425805/
https://www.ncbi.nlm.nih.gov/pubmed/32802002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425805/
https://www.ncbi.nlm.nih.gov/pubmed/32802002

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