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On Strong Mixing Conditions for Stationary Gaussian ...

2006-7-28  (1970) On the Spectrum of Stationary Gaussian Sequences Satisfying the Strong Mixing Condition. II. Sufficient Conditions. Mixing Rate. Theory of Probability Its Applications 15:1, 23-36. Citation PDF (1018 KB)

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On strong mixing conditions for stationary Gaussian ...

Local polynomial fitting has many exciting statistical properties which where established under i.i.d. setting. However, the need for nonlinear time series modeling, constructing predictive intervals, understanding divergence of nonlinear time series requires the development of the theory of local polynomial fitting for dependent data.

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On Strong Mixing Conditions for Stationary Gaussian ...

DOI: 10.1137/1105018 Corpus ID: 120281511. On Strong Mixing Conditions for Stationary Gaussian Processes @article{Kolmogorov1960OnSM, title={On Strong Mixing Conditions for Stationary Gaussian Processes}, author={A. Kolmogorov and Y. Rozanov}, journal={Theory of Probability and Its Applications}, year={1960}, volume={5}, pages={204-208} }

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On Conditions of Strong Mixing of A Gaussian Stationary ...

Rozanov Y.A. (1992) On Conditions of Strong Mixing of A Gaussian Stationary Process. In: Shiryayev A.N. (eds) Selected Works of A. N. Kolmogorov. Mathematics and Its Applications (Soviet Series), vol 26.

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On Strong Mixing Conditions for Stationary Gaussian ...

On Strong Mixing Conditions for Stationary Gaussian Processes 发布:经管之家 分类:Gauss软件培训 搜索 关于本站 人大经济论坛-经管之家:分享大学、考研、论文、会计、留学、数据、经济学、金融学、管理学、统计学、博弈论、统计年鉴、行业分析包括 ...

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Stationary Gaussian Processes Satisfying the Strong Mixing ...

Cite this chapter as: Yaglom A.M. (1965) Stationary Gaussian Processes Satisfying the Strong Mixing Condition and Best Predictable Functionals.

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strong mixing conditions - Encyclopedia of Mathematics

2020-5-21  Strong Mixing Conditions Richard C. Bradley ... structure — for example, Markov chains, Gaussian processes, or linear models, including ARMA (autoregressive – moving average) models. However, it became clear in the middle ... for strictly stationary sequences, the strong mixing (α-mixing

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A NOTE ON STRONG MIXING - Lehigh University

2020-3-12  stationary gaussian sequence is strong mixing if it has a continuous spectral density that is bounded awayfrom 0. Chanda and Withers have considered strong mixing properties of the processYn=

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On the rate of strong mixing in stationary Gaussian random ...

Rosenblatt showed that a stationary Gaussian random field is strongly mixing if it has a positive, continuous spectral density. In this article, spectral criteria are given for the rate of strong mixing in such a field. ... On a strong mixing condition for stationary Gaussian processes, Theory Probab. Appl. 5

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Strong mixing conditions - Encyclopedia of Mathematics

2016-4-4  Here are just a couple of comments: For stationary Gaussian sequences, the α - and ρ -mixing conditions are equivalent to each other, and the ϕ - and ψ -mixing conditions are each equivalent to m -dependence. If a stationary Gaussian sequence has a continuous positive spectral density function, then it is ρ -mixing.

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strong mixing conditions - Encyclopedia of Mathematics

2020-5-21  Strong Mixing Conditions Richard C. Bradley ... structure — for example, Markov chains, Gaussian processes, or linear models, including ARMA (autoregressive – moving average) models. However, it became clear in the middle ... for strictly stationary sequences, the strong mixing (α-mixing

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On the rate of strong mixing in stationary Gaussian random ...

Rosenblatt showed that a stationary Gaussian random field is strongly mixing if it has a positive, continuous spectral density. In this article, spectral criteria are given for the rate of strong mixing

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A Note on Strong-Mixing Gaussian Sequences

This note extends a theorem of Welsch (1971) on the joint asymptotic distribution of some order statistics of a strong-mixing, stationary, Gaussian sequence.

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A strong mixing condition for second-order stationary ...

[10] I. A. Ibragimov, On the spectrum of stationary Gaussian sequences satisfying the strong mixing condition, Theory Probab. Appl. 10 (1965), 85-106; 15 (1970), 24-37. [11] I. A. Ibragimov and V. N. Solev, A condition for the regularity of a Gaussian stationary process, Soviet Math. Dokl. 10 (1969), 371-375.

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A Note on Strassen's Law for Stationary Gaussian

A NOTE ON STRASSENS LAW FOR STATIONARY GAUSSIAN SEQUENCES By CHANDRAKANT M. DEO University of Ottawa, Canada SUMMARY. It is shown that Strassen's law of iterated logarithm applies to strong-mixing stationary Gaussian sequences under conditions weaker than those obtained so far. We assume the framework and notation in Deo (1973). The question of

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Conditions for a Class of Stationary Gaussian Processes to ...

Necessary and sufficient conditions are given for a class of stationary Gaussian processes to be mixing in the sense of Kolmogorov.

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Richard C. Bradley, Mixing Conditions

2012-12-31  9. Stationary Gaussian sequences 10. Central limit theorems under the strong mixing condition 11. Central limit theorems under P-mixing, P*-mixing and related conditions 12. General limiting behavior of partial sums under strong mixing 13. A brief

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CENTRAL LIMIT THEOREM FOR STATIONARY

2018-10-20  called strong mixing wasproposed in [12] andamountedto (2.1) sup IP(BF)-P(B)P(F)l-0 BeQo,Fea5 as n-oo wherePis theprobability measureofthestationaryprocess. Thecon-dition has interest on its ownbut it wasoriginally proposedtogetherwith some additional moment conditions to get asymptotic normality for partial sumsof the randomvariables ofa ...

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Lecture 13 Time Series: Stationarity, AR(p) MA(q)

2018-11-27  A: We need to impose conditions on ρk. Conditions weaker than "they are all zero;" but, strong enough to exclude the sequence of identical copies. Time Series – Ergodicity of the Mean • Definition: A covariance-stationary process is ergodic for the mean if plimz E(Zt) Ergodicity Theorem: Then, a sufficient condition for ergodicity for

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Stat 8112 Lecture Notes Stationary Stochastic Processes ...

2012-4-29  The Birkho ergodic theorem is to strictly stationary stochastic pro-cesses what the strong law of large numbers (SLLN) is to independent and identically distributed (IID) sequences. In e ect, despite the di erent name, it is the SLLN for stationary stochastic processes. Suppose X 1, X 2, :::is a strictly stationary stochastic process and X 1

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Conditions for a Class of Stationary Gaussian Processes to ...

Necessary and sufficient conditions are given for a class of stationary Gaussian processes to be mixing in the sense of Kolmogorov.

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Asymptotic Distribution Of Sum And Maximum For

2006-11-2  The main result in Hsing (1995) is that for strong mixing sequences, such that Sn satisfies the central limit theorem, asymptotic independence of (Sn, Mn) ensues. Gaussian sequences have long been studied with regard to the asymptotic properties of extreme values. It is well known that for stationary Gaussian sequences 6 Xn > with E Xn = 0 and E Xn

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(PDF) Basic Properties of Strong Mixing Conditions. A ...

Basic Properties of Strong Mixing Conditions. A Survey and Some Open Questions. Richard Bradley. Related Papers. Recent advances in invariance principles for stationary sequences. By Sake Delic. Some Aspects of Modeling Dependence in Copula-based Markov chains. By Martial Longla.

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CENTRAL LIMIT THEOREM FOR STATIONARY

2018-10-20  called strong mixing wasproposed in [12] andamountedto (2.1) sup IP(BF)-P(B)P(F)l-0 BeQo,Fea5 as n-oo wherePis theprobability measureofthestationaryprocess. Thecon-dition has interest on its ownbut it wasoriginally proposedtogetherwith some additional moment conditions to get asymptotic normality for partial sumsof the randomvariables ofa ...

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Some mixing conditions for stationary symmetric stable ...

1994-7-1  We derive some necessary and sufficient conditions for mixing of non-Gaussian stationary symmetric stable processes in terms of the spectral representation, and derive additional conditions for the special case where the spectral representation itself is stationary.

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Strong Gaussian approximations of product-limit and ...

2010-4-1  Under strong mixing condition, the strong approximation of the normed quantile process ρ n (p) by a two parameter Gaussian process at the rate O ((log n) − λ) for some λ > 0, was obtained by Fotopoulos et al. (1994) and was later improved by Yu (1996).

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Lecture 13 Time Series: Stationarity, AR(p) MA(q)

2018-11-27  A: We need to impose conditions on ρk. Conditions weaker than "they are all zero;" but, strong enough to exclude the sequence of identical copies. Time Series – Ergodicity of the Mean • Definition: A covariance-stationary process is ergodic for the mean if plimz E(Zt) Ergodicity Theorem: Then, a sufficient condition for ergodicity for

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Lesson 4: Stationary stochastic processes

2014-2-14  de nition of strong stationarity, therefore, strong stationarity does not necessarily imply weak stationarity. For example, an iid process with standard Cauchy distribution is strictly stationary but not weak stationary because the second moment of the process is not nite. Umberto Triacca Lesson 4: Stationary stochastic processes

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Gaussian Random Processes I.A. Ibragimov Springer

The book deals mainly with three problems involving Gaussian stationary processes. The first problem consists of clarifying the conditions for mutual absolute continuity (equivalence) of probability distributions of a "random process segment" and of finding effective formulas for densities of

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Stat 8112 Lecture Notes Stationary Stochastic Processes ...

2012-4-29  The Birkho ergodic theorem is to strictly stationary stochastic pro-cesses what the strong law of large numbers (SLLN) is to independent and identically distributed (IID) sequences. In e ect, despite the di erent name, it is the SLLN for stationary stochastic processes. Suppose X 1, X 2, :::is a strictly stationary stochastic process and X 1

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