Self-normalized Limit Theorems
Self-Normalized Limit Theorems is a class of limit theorems in probability theory where the normalization of partial sums of random variables is achieved internally by their corresponding empirical measures, such as sample variances, rather than by deterministic sequences or population parameters.
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2017–2026
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Limit Distributions of Self-normalized Sums
B. F. Logan, C. L. Mallows, S. O. Rice et al. · The Annals of Probability · 1973 · 196 citations · Full text
Self-normalized large deviations
Qi-Man Shao · The Annals of Probability · 1997 · 173 citations
Self-normalized limit theorems: A survey
Qi-Man Shao, Qiying Wang · Probability Surveys · 2013 · 41 citations · Full text
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Zhejiang University
Hangzhou, China
3 h-index
7 publications
120 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
2 publications
30 citations

The University of Sydney
Sydney, Australia
2 h-index
3 publications
106 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
2 publications
38 citations
Jilin University
Changchun, China
2 h-index
4 publications
48 citations

Vilnius University
Vilnius, Lithuania
2 h-index
2 publications
38 citations
National University of Singapore
Singapore, Singapore
2 h-index
2 publications
27 citations
Wuhan University
Wuhan, China
1 h-index
3 publications
45 citations
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4 publications · 484 citations
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3 publications · 46 citations
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2 publications · 30 citations
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2 publications · 45 citations
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2 publications · 27 citations
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