Arbeitspapier
Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables
In this paper, the complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables are investigated. Some sufficient conditions for the convergence are provided. In addition, the Marcinkiewicz-Zygmund type strong law of large numbers for weighted sums of extended negatively dependent random variables is obtained. The results obtained in the article extend the corresponding ones for independent random variables and some dependent random variables.
- Sprache
-
Englisch
- Erschienen in
-
Series: IRTG 1792 Discussion Paper ; No. 2018-040
Klassifikation
Wirtschaft
Mathematical and Quantitative Methods: General
Mathematical and Quantitative Methods: General
Thema
Extended negatively dependent
complete convergence
complete moment convergence
maximal weighted sums
strong law of large numbers
complete convergence
complete moment convergence
maximal weighted sums
strong law of large numbers
Ereignis
Geistige Schöpfung
(wer)
Yan, Ji Gao
Ereignis
Veröffentlichung
(wer)
Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
(wo)
Berlin
(wann)
2018
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:22 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Yan, Ji Gao
- Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
Entstanden
- 2018
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