Functional convergence for moving averages with heavy tails and random coefficients
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Publication:5742625
zbMath1423.60060arXiv1808.07023MaRDI QIDQ5742625
Publication date: 15 May 2019
Full work available at URL: https://arxiv.org/abs/1808.07023
Processes with independent increments; Lévy processes (60G51) Functional limit theorems; invariance principles (60F17)
Related Items (4)
Maxima of linear processes with heavy‐tailed innovations and random coefficients ⋮ A functional limit theorem for self-normalized linear processes with random coefficients and i.i.d. heavy-tailed innovations ⋮ Unnamed Item ⋮ A functional limit theorem for moving averages with weakly dependent heavy-tailed innovations
Cites Work
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- Functional weak convergence of partial maxima processes
- A functional limit theorem for dependent sequences with infinite variance stable limits
- Probability bounds for M-Skorohod oscillations
- Doob's type inequality and strong law of large numbers for demimartingales
- Tail probabilities for infinite series of regularly varying random vectors
- Weak convergence of sums of moving averages in the \(\alpha\)-stable domain of attraction
- A limit theorem for moving averages in the \(\alpha\)-stable domain of attraction
- Stochastic-Process Limits
- Foundations of Modern Probability
- Heavy-Tail Phenomena
- Limit Theorems for Moving Averages with Random Coefficients and Heavy-Tailed Noise
- An $L^p$-Convergence Theorem
- Association of Random Variables, with Applications
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