FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2094547532> ?p ?o ?g. }

• W2094547532 endingPage "328" @default.
• W2094547532 startingPage "312" @default.
• W2094547532 abstract "Previous article Next article Mixing Conditions for Markov ChainsYu. A. DavydovYu. A. Davydovhttps://doi.org/10.1137/1118033PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] 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 Scholar[2] 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 Scholar[3] 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 Scholar[4] 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 Scholar[5] J. L. Doob, Stochastic processes, John Wiley & Sons Inc., New York, 1953viii+654 MR0058896 0053.26802 Google Scholar[6] I. A. Ibragimov and , Yu. V. Linnik, Independent and stationary sequences of random variables, Wolters-Noordhoff Publishing, Groningen, 1971, 443– MR0322926 0219.60027 Google Scholar[7] William Feller, An introduction to probability theory and its applications. Vol. II., Second edition, John Wiley & Sons Inc., New York, 1971xxiv+669 MR0270403 0219.60003 Google Scholar[8] K. L. Chung, Homogeneous Markov Chains with Countable Numbers of States, Izd-vo “Mir”, Moscow, 1964, (In Russian.) Google Scholar[9] P. Erdös, , W. Feller and , H. Pollard, A property of power series with positive coefficients, Bull. Amer. Math. Soc., 55 (1949), 201–204 MR0027867 0032.27802 CrossrefGoogle Scholar[10] T. E. Harris, The existence of stationary measures for certain Markov processes, Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1954–1955, vol. II, University of California Press, Berkeley and Los Angeles, 1956, 113–124 MR0084889 0072.35201 Google Scholar[11] S. Orey, Recurrent Markov chains, Pacific J. Math., 9 (1959), 805–827 MR0125632 0095.32902 CrossrefGoogle Scholar[12] Benton Jamison and , Steven Orey, Markov chains recurrent in the sense of Harris, Z. Wahrscheinlichkeitstheorie und Verw. Gebiete, 8 (1967), 41–48 10.1007/BF00533943 MR0215370 0153.19802 CrossrefGoogle Scholar[13] N. C. Jain, Some limit theorems for a general Markov process, Z. Wahrscheinlichkeitstheorie und Verw. Gebiete, 6 (1966), 206–223 10.1007/BF00531804 MR0216580 0234.60086 CrossrefGoogle Scholar[14] Stephen R. Kimbleton, A stable limit theorem for Markov chains, Ann. Math. Statist., 40 (1969), 1467–1473 MR0245098 0192.55103 CrossrefGoogle Scholar[15] M. Rosenblatt, A strong mixing condition and a central limit theorem on compact groups, J. Math. 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. III. Distributions of Functionals of Processes, Stochastic Geometry, and Extrema6 February 2019 | Vestnik St. Petersburg University, Mathematics, Vol. 51, No. 4 Cross Ref On the History of St. Petersburg School of Probability and Mathematical Statistics: II. Random Processes and Dependent Variables4 September 2018 | Vestnik St. Petersburg University, Mathematics, Vol. 51, No. 3 Cross Ref Model comparison for generalized linear models with dependent observationsEconometrics and Statistics, Vol. 5 Cross Ref Maximum Likelihood Estimation in Possibly Misspecified Dynamic Models with Time Inhomogeneous Markov RegimesSSRN Electronic Journal Cross Ref A measure of dependence for cryptographic primitives relative to ideal functionsRocky Mountain Journal of Mathematics, Vol. 45, No. 4 Cross Ref NONPARAMETRIC ESTIMATION OF DYNAMIC PANEL MODELS WITH FIXED EFFECTS27 May 2014 | Econometric Theory, Vol. 30, No. 6 Cross Ref References12 June 2014 Cross Ref On a ‘Replicating Character String’ Model19 February 2016 | Journal of Applied Probability, Vol. 51, No. 2 Cross Ref Divergent Perpetuities Modulated by Regime SwitchesStochastic Models, Vol. 29, No. 2 Cross Ref ARCHIMEDEAN COPULAS AND TEMPORAL DEPENDENCE27 April 2012 | Econometric Theory, Vol. 28, No. 6 Cross Ref Markov chain approach to identifying Wiener systems4 May 2012 | Science China Information Sciences, Vol. 55, No. 5 Cross Ref ON THE SPECTRAL MEASURES OF SOME WEAKLY STATIONARY SEQUENCES INVOLVING RANDOMLY SPACED OBSERVATIONSStochastics and Dynamics, Vol. 12, No. 01 Cross Ref A semiparametric method for estimating nonlinear autoregressive model with dependent errorsNonlinear Analysis: Theory, Methods & Applications, Vol. 74, No. 17 Cross Ref References25 May 2012 Cross Ref Stationarity and geometric ergodicity of BEKK multivariate GARCH modelsStochastic Processes and their Applications, Vol. 121, No. 10 Cross Ref Generalized runs tests for the IID hypothesisJournal of Econometrics, Vol. 162, No. 2 Cross Ref MULTIVARIATE ECOGARCH PROCESSES13 September 2010 | Econometric Theory, Vol. 27, No. 02 Cross Ref VARIANCE BOUNDING MARKOV CHAINS, L 2 -UNIFORM MEAN ERGODICITY AND THE CLTStochastics and Dynamics, Vol. 11, No. 01 Cross Ref Murray Rosenblatt’s Contributions to Strong Mixing24 March 2011 Cross Ref Nonlinear Persistence and Copersistence Cross Ref Recursive Identification for Nonlinear ARX Systems Based on Stochastic Approximation AlgorithmIEEE Transactions on Automatic Control, Vol. 55, No. 6 Cross Ref Semiparametric estimation of regression functions in autoregressive modelsStatistics & Probability Letters, Vol. 79, No. 2 Cross Ref Rates of convergence for minimal distances in the central limit theorem under projective criteriaElectronic Journal of Probability, Vol. 14, No. none Cross Ref Efficient Estimation of Copula-Based Semiparametric Markov ModelsSSRN Electronic Journal Cross Ref Nonparametric Algorithms for Identification of Nonlinear Autoregressive Systems with Exogenous InputsIFAC Proceedings Volumes, Vol. 42, No. 10 Cross Ref Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path14 November 2007 | Machine Learning, Vol. 71, No. 1 Cross Ref Parametric and nonparametric models and methods in financial econometricsStatistics Surveys, Vol. 2, No. none Cross Ref An Exponential Continuous-Time GARCH Process14 July 2016 | Journal of Applied Probability, Vol. 44, No. 4 Cross Ref Testing for Regime SwitchingEconometrica, Vol. 75, No. 6 Cross Ref On a Stationary, Triple-Wise Independent, Absolutely Regular Counterexample to the Central Limit TheoremRocky Mountain Journal of Mathematics, Vol. 37, No. 1 Cross Ref Lower Bounds of Mixing Rate for a Class of Markov ProcessesS. A. Klokov28 August 2007 | Theory of Probability & Its Applications, Vol. 51, No. 3AbstractPDF (147 KB)Ergodicity and exponential β -mixing bounds for multidimensional diffusions with jumpsStochastic Processes and their Applications, Vol. 117, No. 1 Cross Ref Multivariate CARMA processesStochastic Processes and their Applications, Vol. 117, No. 1 Cross Ref Integer-Valued Time SeriesSSRN Electronic Journal Cross Ref Nonparametric Estimation of Dynamic Panel Models with Fixed EffectsSSRN Electronic Journal Cross Ref Stationarity and geometric ergodicity of a class of nonlinear ARCH modelsThe Annals of Applied Probability, Vol. 16, No. 4 Cross Ref Renewal regime switching and stable limit lawsJournal of Econometrics, Vol. 129, No. 1-2 Cross Ref ASYMPTOTICS OF THE QMLE FOR A CLASS OF ARCH(q) MODELS22 August 2005 | Econometric Theory, Vol. 21, No. 05 Cross Ref Towards a Unified Approach for Proving Geometric Ergodicity and Mixing Properties of Nonlinear Autoregressive ProcessesJournal of Time Series Analysis, Vol. 26, No. 5 Cross Ref Super optimal rates for nonparametric density estimation via projection estimatorsStochastic Processes and their Applications, Vol. 115, No. 5 Cross Ref Semi-Parametric Modelling of Correlation DynamicsSSRN Electronic Journal Cross Ref Geometric Ergodicity of a Class of Markov Chains with Applications to Time Series ModelsSSRN Electronic Journal Cross Ref Nonparametric multistep-ahead prediction in time series analysisJournal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 66, No. 3 Cross Ref A regularity condition and a limit theorem for Harris ergodic Markov chainsStochastic Processes and their Applications, Vol. 111, No. 2 Cross Ref On the Markov chain central limit theoremProbability Surveys, Vol. 1, No. none Cross Ref The conditional central limit theorem in Hilbert spacesStochastic Processes and their Applications, Vol. 108, No. 2 Cross Ref Geometric absolute regularity of Banach space-valued autoregressive processesStatistics & Probability Letters, Vol. 60, No. 3 Cross Ref Properties of the nonparametric autoregressive bootstrapJournal of Time Series Analysis, Vol. 23, No. 5 Cross Ref Some Aspects of Statistical Inference in a Markovian and Mixing Framework Cross Ref Propriétés de mélanges des processus autorégressifs banachiquesComptes Rendus de l'Académie des Sciences - Series I - Mathematics, Vol. 333, No. 4 Cross Ref Random Fields on Z d , Limit Theorems and Irregular Sets Cross Ref Spectral Density for Third Order Cumulants under Strong Mixing ConditionsJournal of Multivariate Analysis, Vol. 74, No. 2 Cross Ref Approximation of Distributions of Sums of Weakly Dependent Random Variables by the Normal Distribution Cross Ref Functional estimation for time series: Uniform convergence propertiesJournal of Statistical Planning and Inference, Vol. 68, No. 1 Cross Ref Nonparametric vector autoregressionJournal of Statistical Planning and Inference, Vol. 68, No. 2 Cross Ref Memory-universal prediction of stationary random processesIEEE Transactions on Information Theory, Vol. 44, No. 1 Cross Ref Local polynomial estimators of the volatility function in nonparametric autoregressionJournal of Econometrics, Vol. 81, No. 1 Cross Ref Convergence of changepoint estimators for weakly dependent dataJournal of Nonparametric Statistics, Vol. 8, No. 4 Cross Ref Minimum complexity regression estimation with weakly dependent observationsIEEE Transactions on Information Theory, Vol. 42, No. 6 Cross Ref Wavelet linear density estimator for a discrete-time stochastic process: Lp-lossesStatistics & Probability Letters, Vol. 27, No. 1 Cross Ref Asymptotic Normality of Nearest Neighbor Regression Function Estimates Based on Nonstationary Dependent ObservationsAmerican Journal of Mathematical and Management Sciences, Vol. 15, No. 3-4 Cross Ref Weak invariance of the multidimensional rank statistic for nonstationary absolutely regular processesJournal of Multivariate Analysis, Vol. 36, No. 2 Cross Ref Research Directions in Robust Statistics Cross Ref Dependence Among Observations: Consequences and Methods to Deal With it Cross Ref Measures of Dependence For Processes in metric spaces4 April 2007 | Stochastics and Stochastic Reports, Vol. 27, No. 1 Cross Ref A stationary, pairwise independent, absolutely regular sequence for which the central limit theorem fails1 February 1989 | Probability Theory and Related Fields, Vol. 81, No. 1 Cross Ref Finitely determined processes in metric spacesStatistics & Probability Letters, Vol. 7, No. 4 Cross Ref On a theorem of gordinStochastics, Vol. 24, No. 4 Cross Ref Bounds for the Mixing Rate in the Theory of Stochastic EquationsA. Yu. Veretennikov17 July 2006 | Theory of Probability & Its Applications, Vol. 32, No. 2AbstractPDF (832 KB)Limit Theorems for Harris Markov Chains, IV. K. Malinovskii3 August 2006 | Theory of Probability & Its Applications, Vol. 31, No. 2AbstractPDF (1611 KB)Moment inequalities for mixing sequences of random variablesStochastic Analysis and Applications, Vol. 5, No. 1 Cross Ref Invariance principles under weak dependenceJournal of Multivariate Analysis, Vol. 19, No. 2 Cross Ref On a very weak bernoulli condition †2 May 2007 | Stochastics, Vol. 13, No. 1-2 Cross Ref Absolute regularity and functions of Markov chainsStochastic Processes and their Applications, Vol. 14, No. 1 Cross Ref Eine Restgliedabschätzung in der ErneuerungstheorieArchiv der Mathematik, Vol. 39, No. 2 Cross Ref Über das asymptotische Verhalten von ErneuerungsdichtenMathematische Nachrichten, Vol. 108, No. 1 Cross Ref Central limit theorems under weak dependenceJournal of Multivariate Analysis, Vol. 11, No. 1 Cross Ref On the Convergence Rate in the Central Limit Theorem for Weakly Dependent Random VariablesA. N. Tikhomirov17 July 2006 | Theory of Probability & Its Applications, Vol. 25, No. 4AbstractPDF (1254 KB)Spaces of Summable Sequences in Renewal Theory and the Theory of Markov ChainsMathematische Nachrichten, Vol. 104, No. 1 Cross Ref The weak convergence of the likelihood ratio random fields for Markov observationsAnnals of the Institute of Statistical Mathematics, Vol. 29, No. 1 Cross Ref Summary of Reports Presented at Sessions of the Probability and Statistics Seminar in the Leningrad Section of the Mathematical Institute of the USSR Academy of Sciences17 July 2006 | Theory of Probability & Its Applications, Vol. 20, No. 3AbstractPDF (1857 KB)Semi-Parametric Modelling of Correlation Dynamics Cross Ref Volume 18, Issue 2| 1974Theory of Probability & Its Applications History Submitted:25 January 1971Published online:17 July 2006 InformationCopyright © 1974 Society for Industrial and Applied MathematicsPDF Download Article & Publication DataArticle DOI:10.1137/1118033Article page range:pp. 312-328ISSN (print):0040-585XISSN (online):1095-7219Publisher:Society for Industrial and Applied Mathematics" @default.
• W2094547532 created "2016-06-24" @default.
• W2094547532 creator A5090737911 @default.
• W2094547532 date "1974-03-01" @default.
• W2094547532 modified "2023-10-18" @default.
• W2094547532 title "Mixing Conditions for Markov Chains" @default.
• W2094547532 cites W1964381934 @default.
• W2094547532 cites W1984140867 @default.
• W2094547532 cites W2022375021 @default.
• W2094547532 cites W2030027191 @default.
• W2094547532 cites W2075601995 @default.
• W2094547532 cites W4230410498 @default.
• W2094547532 cites W4244512033 @default.
• W2094547532 doi "https://doi.org/10.1137/1118033" @default.
• W2094547532 hasPublicationYear "1974" @default.
• W2094547532 type Work @default.
• W2094547532 sameAs 2094547532 @default.
• W2094547532 citedByCount "173" @default.
• W2094547532 countsByYear W20945475322012 @default.
• W2094547532 countsByYear W20945475322013 @default.
• W2094547532 countsByYear W20945475322014 @default.
• W2094547532 countsByYear W20945475322015 @default.
• W2094547532 countsByYear W20945475322016 @default.
• W2094547532 countsByYear W20945475322017 @default.
• W2094547532 countsByYear W20945475322018 @default.
• W2094547532 countsByYear W20945475322019 @default.
• W2094547532 countsByYear W20945475322020 @default.
• W2094547532 countsByYear W20945475322021 @default.
• W2094547532 countsByYear W20945475322022 @default.
• W2094547532 countsByYear W20945475322023 @default.
• W2094547532 crossrefType "journal-article" @default.
• W2094547532 hasAuthorship W2094547532A5090737911 @default.
• W2094547532 hasConcept C105795698 @default.
• W2094547532 hasConcept C121332964 @default.
• W2094547532 hasConcept C121864883 @default.
• W2094547532 hasConcept C138777275 @default.
• W2094547532 hasConcept C33923547 @default.
• W2094547532 hasConcept C62520636 @default.
• W2094547532 hasConcept C98763669 @default.
• W2094547532 hasConceptScore W2094547532C105795698 @default.
• W2094547532 hasConceptScore W2094547532C121332964 @default.
• W2094547532 hasConceptScore W2094547532C121864883 @default.
• W2094547532 hasConceptScore W2094547532C138777275 @default.
• W2094547532 hasConceptScore W2094547532C33923547 @default.
• W2094547532 hasConceptScore W2094547532C62520636 @default.
• W2094547532 hasConceptScore W2094547532C98763669 @default.
• W2094547532 hasIssue "2" @default.
• W2094547532 hasLocation W20945475321 @default.
• W2094547532 hasOpenAccess W2094547532 @default.
• W2094547532 hasPrimaryLocation W20945475321 @default.
• W2094547532 hasRelatedWork W1522994095 @default.
• W2094547532 hasRelatedWork W1523881906 @default.
• W2094547532 hasRelatedWork W2031897005 @default.
• W2094547532 hasRelatedWork W2049353827 @default.
• W2094547532 hasRelatedWork W2130581915 @default.
• W2094547532 hasRelatedWork W2257838449 @default.
• W2094547532 hasRelatedWork W2347229780 @default.
• W2094547532 hasRelatedWork W2381569343 @default.
• W2094547532 hasRelatedWork W3100157974 @default.
• W2094547532 hasRelatedWork W4297803385 @default.
• W2094547532 hasVolume "18" @default.
• W2094547532 isParatext "false" @default.
• W2094547532 isRetracted "false" @default.
• W2094547532 magId "2094547532" @default.
• W2094547532 workType "article" @default.