A characterization of Gaussian processes that are Markovian
Waclaw Timoszyk (1974)
Colloquium Mathematicae
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Waclaw Timoszyk (1974)
Colloquium Mathematicae
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Renze, John, Wagon, Stan, Wick, Brian (2001)
Experimental Mathematics
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Rovskiĭ, V.A. (2004)
Zapiski Nauchnykh Seminarov POMI
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Eisenbaum, Nathalie (2005)
Electronic Journal of Probability [electronic only]
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J.-R. Pycke (2006)
Banach Center Publications
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Karhunen-Loève expansions of Gaussian processes have numerous applications in Probability and Statistics. Unfortunately the set of Gaussian processes with explicitly known spectrum and eigenfunctions is narrow. An interpretation of three historical examples enables us to understand the key role of the Laplacian. This allows us to extend the set of Gaussian processes for which a very explicit Karhunen-Loève expansion can be derived.
Manfred G. Madritsch (2008)
Acta Arithmetica
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Slobodanka S. Mitrović (2005)
Matematički Vesnik
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Nathan Keller, Elchanan Mossel, Arnab Sen (2014)
Annales de l'I.H.P. Probabilités et statistiques
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In a recent paper, we presented a new definition of influences in product spaces of continuous distributions, and showed that analogues of the most fundamental results on discrete influences, such as the KKL theorem, hold for the new definition in Gaussian space. In this paper we prove Gaussian analogues of two of the central applications of influences: Talagrand’s lower bound on the correlation of increasing subsets of the discrete cube, and the Benjamini–Kalai–Schramm (BKS) noise sensitivity...
Nicolas Privault, Anthony Réveillac (2011)
ESAIM: Probability and Statistics
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Using integration by parts on Gaussian space we construct a Stein Unbiased Risk Estimator (SURE) for the drift of Gaussian processes, based on their local and occupation times. By almost-sure minimization of the SURE risk of shrinkage estimators we derive an estimation and de-noising procedure for an input signal perturbed by a continuous-time Gaussian noise.
Michel Talagrand (1988)
Annales de l'I.H.P. Probabilités et statistiques
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S. Mitrović (1984)
Matematički Vesnik
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Yuichi Futa, Hiroyuki Okazaki, Daichi Mizushima, Yasunari Shidama (2013)
Formalized Mathematics
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Gaussian integer is one of basic algebraic integers. In this article we formalize some definitions about Gaussian integers [27]. We also formalize ring (called Gaussian integer ring), Z-module and Z-algebra generated by Gaussian integer mentioned above. Moreover, we formalize some definitions about Gaussian rational numbers and Gaussian rational number field. Then we prove that the Gaussian rational number field and a quotient field of the Gaussian integer ring are isomorphic. ...
Joseph Lehec (2013)
Annales de l'I.H.P. Probabilités et statistiques
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We prove a stochastic formula for the Gaussian relative entropy in the spirit of Borell’s formula for the Laplace transform. As an application, we give simple proofs of a number of functional inequalities.
M. Clausel, F. Roueff, M. S. Taqqu, C. Tudor (2014)
ESAIM: Probability and Statistics
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We consider stationary processes with long memory which are non-Gaussian and represented as Hermite polynomials of a Gaussian process. We focus on the corresponding wavelet coefficients and study the asymptotic behavior of the sum of their squares since this sum is often used for estimating the long–memory parameter. We show that the limit is not Gaussian but can be expressed using the non-Gaussian Rosenblatt process defined as a Wiener–Itô integral of order 2. This happens even if the...