Mixing Conditions for Markov Chains

Previous article Next article Mixing Conditions for Markov ChainsYu. A. DavydovYu. A. Davydovhttps://doi.org/10.1137/1118033PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout1 V. A. Volkonskii and , Yu. A. Rozanov, Some limit theorems for random functions. I, Theor. Probability Appl., 4 (1959), 178–197 10.1137/1104015 MR0121856 0092.33502 LinkGoogle Scholar2 I. Gel'fand, , D. Raikov and , G. Shilov, Commutative normed rings, Translated from the Russian, with a supplementary chapter, Chelsea Publishing Co., New York, 1964, 306– MR0205105 Google Scholar3 R. L. Dobrushin, Central limit theorem for non-stationary Markov chains, I, Theory Prob. Applications, 1 (1956), 65–80, II, 1 (1956), pp. 329–383 10.1137/1101006 LinkGoogle Scholar4 Yu. A. Davydov, On the strong mixing property for Markov chains with a countable number of states, Soviet Mathematics, 10 (1969), 825–827 0191.47402 Google Scholar5 J. L. 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Mech., 17 (1967), 189–198 MR0212845 0153.47304 Google Scholar Previous article Next article FiguresRelatedReferencesCited byDetails Age of Information Process under Strongly Mixing Communication - Moment Bound, Mixing Rate and Strong Law Cross Ref Spectral estimation of Hawkes processes from count dataThe Annals of Statistics, Vol. 50, No. 3 Cross Ref Detecting systematic anomalies affecting systems when inputs are stationary time series17 February 2022 | Applied Stochastic Models in Business and Industry, Vol. 38, No. 3 Cross Ref A Semiparametric Approach for Modeling Partially Linear Autoregressive Model with Skew Normal InnovationsAdvances in Mathematical Physics, Vol. 2022 Cross Ref Variable selection via quantile regression with the process of Ornstein-Uhlenbeck type9 September 2021 | Science China Mathematics, Vol. 2 Cross Ref Subgeometric ergodicity and β -mixing16 September 2021 | Journal of Applied Probability, Vol. 58, No. 3 Cross Ref Extremal clustering in non-stationary random sequences12 May 2021 | Extremes, Vol. 3 Cross Ref A new CLT for additive functionals of Markov chainsStochastic Processes and their Applications, Vol. 130, No. 9 Cross Ref Functional CLT for nonstationary strongly mixing processesStatistics & Probability Letters, Vol. 156 Cross Ref Detecting Systematic Anomalies Affecting Systems When Inputs Are Stationary Time SeriesSSRN Electronic Journal Cross Ref A semiparametric approach for modelling multivariate nonlinear time series23 July 2019 | Canadian Journal of Statistics, Vol. 47, No. 4 Cross Ref Power periodic threshold GARCH model: Structure and estimation29 December 2018 | Communications in Statistics - Theory and Methods, Vol. 48, No. 19 Cross Ref Commercial and Residential Mortgage Defaults: Spatial Dependence with FrailtyJournal of Econometrics, Vol. 212, No. 1 Cross Ref A Semiparametric Estimation for the First-Order Nonlinear Autoregressive Time Series Model with Independent and Dependent Errors1 March 2018 | Iranian Journal of Science and Technology, Transactions A: Science, Vol. 43, No. 3 Cross Ref Nonparametric inference on Lévy measures of compound Poisson-driven Ornstein-Uhlenbeck processes under macroscopic discrete observationsElectronic Journal of Statistics, Vol. 13, No. 2 Cross Ref Transformed Perturbation Solutions for Dynamic Stochastic General Equilibrium ModelsSSRN Electronic Journal Cross Ref Estimation and HAC-based Inference for Machine Learning Time Series RegressionsSSRN Electronic Journal Cross Ref On the History of the St. Petersburg School of Probability and Statistics. 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