Moment inequalities for mixing sequences of random variables
- 1 January 1987
- journal article
- research article
- Published by Taylor & Francis in Stochastic Analysis and Applications
- Vol. 5 (1) , 60-120
- https://doi.org/10.1080/07362998708809108
Abstract
In this work, sequences of random variables are considered satisfying certain mixing conditions. After the relevant definitions are presented, some alternative characterizations are discussed. Also, illustrative examples are given for each case considered. Finally , various moment in equalities are extensively discussed in a systematic manner. These equalities are interesting on their own right and also useful in statistical applications. Certain such applications will be presented in a separate report to avoid overloading the present oneKeywords
This publication has 32 references indexed in Scilit:
- A note on strong mixing of ARMA processesStatistics & Probability Letters, 1986
- A note on two measures of dependence and mixing sequencesAdvances in Applied Probability, 1983
- Approximation theorems for strongly mixing random variables.The Michigan Mathematical Journal, 1983
- Invariance Principles for Mixing Sequences of Random VariablesThe Annals of Probability, 1982
- On the ϕ-mixing condition for stationary random sequencesDuke Mathematical Journal, 1980
- Examples of mixing sequencesDuke Mathematical Journal, 1976
- The Asymptotic Distribution Theory of the Empiric CDF for Mixing Stochastic ProcessesThe Annals of Statistics, 1975
- Strong mixing properties of linear stochastic processesJournal of Applied Probability, 1974
- A Note on Empirical Processes of Strong-Mixing SequencesThe Annals of Probability, 1973
- A Connection between Correlation and ContingencyMathematical Proceedings of the Cambridge Philosophical Society, 1935