2018
DOI: 10.1093/imrn/rny248
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On the Probability That a Stationary Gaussian Process With Spectral Gap Remains Non-negative on a Long Interval

Abstract: Let f be a zero mean continuous stationary Gaussian process on R whose spectral measure vanishes in a δ-neighborhood of the origin. Then the probability that f stays non-negative on an interval of length L is at most e −cδ 2 L 2 with some absolute c > 0 and the result is sharp without additional assumptions.1991 Mathematics Subject Classification. 60G10, 60G15.

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Cited by 4 publications
(18 citation statements)
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“…Finally, the third term on the right hand side of (37) can be estimated as 1 − corr X k (s), X k (s + τ ) ρ,σ τ, which verifies (19), and hence completes the proof of the theorem.…”
Section: Proof Of Theorem 21mentioning
confidence: 57%
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“…Finally, the third term on the right hand side of (37) can be estimated as 1 − corr X k (s), X k (s + τ ) ρ,σ τ, which verifies (19), and hence completes the proof of the theorem.…”
Section: Proof Of Theorem 21mentioning
confidence: 57%
“…This observation along with part (b) of Lemma 3.2 shows that θ(C∞,H) = 0. From this, the conclusion follows from part (a) of Lemma 3.10, once we verify (19). But this follows on noting that Cp,H (τ /p) ≥ e − p+H p τ .…”
Section: Proof Of Theorem 210mentioning
confidence: 78%
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