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Comptes Rendus Mathématique
Volume 346, n° 3-4
pages 209-212 (février 2008)
Doi : 10.1016/j.crma.2007.12.007
Received : 6 September 2007 ;  accepted : 11 December 2007
The Neyman–Pearson lemma under g -probability
Lemme de Neyman–Pearson généralisé pour les g -espérances
 

Shaolin Ji a , Xun Yu Zhou b, c
a School of Mathematics and System Sciences, Shandong University, Jinan, Shandong, 250100, PR China 
b Mathematical Institute, University of Oxford, 24–29 St Giles, Oxford OX1 3LB, UK 
c Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong 

Abstract

The Neyman–Pearson fundamental lemma is generalized under g -probability. With convexity assumptions, a sufficient and necessary condition which characterizes the optimal randomized tests is obtained via a maximum principle for stochastic control. To cite this article: S. Ji, X.Y. Zhou, C. R. Acad. Sci. Paris, Ser. I 346 (2008).

The full text of this article is available in PDF format.
Résumé

Le lemme fondamental de Neyman–Pearson est généralisé au cas de g -probabilités. Sous des hypothèses de convexité, une condition suffisante et nécessaire caractérisant le test randomisé optimal est obtenue au moyen du principe du maximum dans le cadre du contrôle stochastique. Pour citer cet article : S. Ji, X.Y. Zhou, C. R. Acad. Sci. Paris, Ser. I 346 (2008).

The full text of this article is available in PDF format.

 The authors thank the partial support from the National Basic Research Program of China (973 Program, No. 2007CB814900), the RGC Earmark Grant No. 418606, and a start-up fund at Oxford.
 This Note is the succinct version of a text on file for five years in the Academy Archives.



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