The Accuracy of Merging Approximation in Generalized St. Petersburg Games
Gyula Pap ()
Additional contact information
Gyula Pap: University of Debrecen
Journal of Theoretical Probability, 2011, vol. 24, issue 1, 240-270
Abstract:
Abstract Merging asymptotic expansions of arbitrary length are established for the distribution functions and for the probabilities of suitably centered and normalized cumulative winnings in a full sequence of generalized St. Petersburg games, extending the short expansions due to Csörgő (Acta Sci. Math. (Szeged) 73:297–331, 2007). These expansions are given in terms of suitably chosen members from the classes of subsequential semistable infinitely divisible asymptotic distribution functions and certain derivatives of these functions. The length of the expansion depends upon the tail parameter. Both uniform and nonuniform bounds are presented.
Keywords: Merging asymptotic expansions; Semistable distribution functions; St. Petersburg games; 60F05; 60E07; 60G50 (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10959-009-0247-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jotpro:v:24:y:2011:i:1:d:10.1007_s10959-009-0247-1
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10959
DOI: 10.1007/s10959-009-0247-1
Access Statistics for this article
Journal of Theoretical Probability is currently edited by Andrea Monica
More articles in Journal of Theoretical Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().