Central limit theorems for weighted sums of dependent random vectors in Hilbert spaces via the theory of the regular variation
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Publication:2135199
DOI10.1007/s10959-021-01079-4zbMath1487.60057OpenAlexW3129868951MaRDI QIDQ2135199
Publication date: 4 May 2022
Published in: Journal of Theoretical Probability (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10959-021-01079-4
Linear regression; mixed models (62J05) Central limit and other weak theorems (60F05) Martingales and classical analysis (60G46)
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Cites Work
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- Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics
- Central limit theorem for linear processes with infinite variance
- The law of large numbers and the central limit theorem in Banach spaces
- Weak laws of large numbers for sequences of random variables with infinite \(r\)th moments
- Convergence results for multivariate martingales
- Asymptotic Analysis of Random Walks
- Martingale Transforms
- An invariance principle for the Robbins-Monro process in a Hilbert space
- Pseudo-Regularly Varying Functions and Generalized Renewal Processes
- Long-Range Dependence and Self-Similarity
- Probability: A Graduate Course
- Regularly varying functions
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