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个人简介
Gábor J. Székely (Hungarian pronunciation: ; born February 4, 1947 in Budapest) is a Hungarian-American statistician/mathematician best known for introducing energy statistics (E-statistics). Examples include: the distance correlation, which is a bona fide dependence measure, equals zero exactly when the variables are independent; the distance skewness, which equals zero exactly when the probability distribution is diagonally symmetric;the E-statistic for normality test; and the E-statistic for clustering.
Other important discoveries include the Hungarian semigroups, the location testing for Gaussian scale mixture distributions, the uncertainty principle of game theory, the half-coin which involves negative probability, and the solution of an old open problem of lottery mathematics: in a 5-from-90 lotto the minimum number of tickets one needs to buy to guarantee that at least one of these tickets has (at least) 2 matches is exactly 100.
Other important discoveries include the Hungarian semigroups, the location testing for Gaussian scale mixture distributions, the uncertainty principle of game theory, the half-coin which involves negative probability, and the solution of an old open problem of lottery mathematics: in a 5-from-90 lotto the minimum number of tickets one needs to buy to guarantee that at least one of these tickets has (at least) 2 matches is exactly 100.
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论文共 377 篇作者统计合作学者相似作者
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MATHEMATICAL METHODS IN THE APPLIED SCIENCESno. 8 (2023): 8855-8876
European journal of haematologyno. 2 (2023): 254-262
The Energy of Data and Distance Correlationpp.121-130, (2022)
Z. Juranyi, Z.S. Kocsis,K. Lumniczky,K. Balázs,P. Ágoston,G. Farkas, V. Tölgyesi,G. Székely,T. Major, C. Pesznyák,G. Stelczer,K. Jorgo,
The Energy of Data and Distance Correlationpp.305-314, (2022)
Gábor J. Székely, Maria L. Rizzo
The Energy of Data and Distance Correlationpp.183-188, (2022)
Gábor J. Székely, Maria L. Rizzo
The Energy of Data and Distance Correlationpp.181-406, (2022)
Mathematical Methods in the Applied Sciences (2022)
The Energy of Data and Distance Correlationpp.375-394, (2022)
The Energy of Data and Distance Correlationpp.315-344, (2022)
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