Bounding the Gini Mean Difference

2008 ◽  
pp. 77-89 ◽  
Author(s):  
Pietro Cerone
2006 ◽  
Vol 22 (3) ◽  
pp. 305-315 ◽  
Author(s):  
P. Cerone ◽  
S. S. Dragomir

2017 ◽  
Vol 471 ◽  
pp. 554-560 ◽  
Author(s):  
A. Khosravi Tanak ◽  
G.R. Mohtashami Borzadaran ◽  
J. Ahmadi

2015 ◽  
Vol 4 (1) ◽  
pp. 45-66
Author(s):  
Kalpana Mahajan ◽  
Sangeeta Arora ◽  
Priyanka Vashista

2019 ◽  
Vol 34 (1) ◽  
pp. 1-7
Author(s):  
Saeid Tahmasebi ◽  
Hojat Parsa

Abstract Di Crescenzo and Longobardi [Di Crescenzo and Longobardi, On cumulative entropies, J. Statist. Plann. Inference 139 2009, 12, 4072–4087] proposed the cumulative entropy (CE) as an alternative to the differential entropy. They presented an estimator of CE using empirical approach. In this paper, we consider a risk measure based on CE and compare it with the standard deviation and the Gini mean difference for some distributions. We also make empirical comparisons of these measures using samples from stock market in members of the Organization for Economic Co-operation and Development (OECD) countries.


2013 ◽  
Vol 42 (11) ◽  
pp. 1998-2008 ◽  
Author(s):  
David D. Tung ◽  
S. Rao Jammalamadaka

2005 ◽  
Vol 50 (3-4) ◽  
pp. 599-609 ◽  
Author(s):  
P. Cerone ◽  
S.S. Dragomir

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