Central limit theorems under weak dependence
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Cited by:
- Sergey Utev & Magda Peligrad, 2003. "Maximal Inequalities and an Invariance Principle for a Class of Weakly Dependent Random Variables," Journal of Theoretical Probability, Springer, vol. 16(1), pages 101-115, January.
- Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022.
"Inference for extremal regression with dependent heavy-tailed data,"
TSE Working Papers
22-1324, Toulouse School of Economics (TSE), revised 29 Aug 2023.
- Abdelaati Daouia & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2023. "Inference for extremal regression with dependent heavy-tailed data," Post-Print hal-04554050, HAL.
- Gonzalo Perera, 1997. "Geometry of $$\mathbb{Z}^d $$ and the Central Limit Theorem for Weakly Dependent Random Fields," Journal of Theoretical Probability, Springer, vol. 10(3), pages 581-603, July.
- Alexander Varypaev, 2024. "Asymptotic Form of the Covariance Matrix of Likelihood-Based Estimator in Multidimensional Linear System Model for the Case of Infinity Number of Nuisance Parameters," Mathematics, MDPI, vol. 12(3), pages 1-22, February.
- Martin Spiess & Pascal Jordan & Mike Wendt, 2019. "Simplified Estimation and Testing in Unbalanced Repeated Measures Designs," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 212-235, March.
- Furrer, Reinhard, 2005. "Covariance estimation under spatial dependence," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 366-381, June.
- Aneiros-Pérez, Germán, 2002. "On bandwidth selection in partial linear regression models under dependence," Statistics & Probability Letters, Elsevier, vol. 57(4), pages 393-401, May.
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Keywords
Strictly stationary strong mixing maximal correlation kernel-type density estimator;Statistics
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