scholarly journals Asymptotic Equivalence of Probabilistic Serial and Random Priority Mechanisms

Econometrica ◽  
2010 ◽  
Vol 78 (5) ◽  
pp. 1625-1672 ◽  
2003 ◽  
Vol 45 (6-9) ◽  
pp. 1327-1337 ◽  
Author(s):  
Sung Kyu Choi ◽  
Nam Jip Koo ◽  
Hyun Sook Ryu

1997 ◽  
Vol 13 (2) ◽  
pp. 170-184 ◽  
Author(s):  
John L. Knight ◽  
Stephen E. Satchell

This paper deals with the use of the empirical cumulant generating function to consistently estimate the parameters of a distribution from data that are independent and identically distributed (i.i.d.). The technique is particularly suited to situations where the density function is unknown or unbounded in parameter space. We prove asymptotic equivalence of our technique to that of the empirical characteristic function and outline a six-step procedure for its implementation. Extensions of the approach to non-i.i.d. situations are considered along with a discussion of suitable applications and a worked example.


2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Martin Branda

We deal with the conditions which ensure exact penalization in stochastic programming problems under finite discrete distributions. We give several sufficient conditions for problem calmness including graph calmness, existence of an error bound, and generalized Mangasarian-Fromowitz constraint qualification. We propose a new version of the theorem on asymptotic equivalence of local minimizers of chance constrained problems and problems with exact penalty objective. We apply the theory to a problem with a stochastic vanishing constraint.


2018 ◽  
Vol 206 ◽  
pp. 363-379 ◽  
Author(s):  
Irwan Katili ◽  
Imam Jauhari Maknun ◽  
Jean-Louis Batoz ◽  
Andi Makarim Katili

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