Probability tail for linearly negative quadrant dependent random variables of partial sums and application to linear model Inequalities for LNQD R.V of partial sums and application

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Zoubeyr Kaddour
Abderrahmane Belguerna
Samir Benaissa


In this paper, we establish a new concentration inequality and complete convergence of weighted sums for arrays of rowwise linearly negative quadrant dependent (LNQD, in short) random variables and obtain a result dealing with complete convergence of first-order autoregressive processes with identically distributed LNQD innovations.


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How to Cite
Kaddour, Z., Belguerna, A. and Benaissa, S. 2022. Probability tail for linearly negative quadrant dependent random variables of partial sums and application to linear model: Inequalities for LNQD R.V of partial sums and application. Journal of Innovative Applied Mathematics and Computational Sciences. 2, 2 (Aug. 2022), 14–22. DOI:
Conference paper (ICMA'2021)
Author Biographies

Zoubeyr Kaddour

Department of Mathematics and computer sciences, S.A University center of Naâma.

Samir Benaissa

D.L University of SBA


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