Absolute regularity and functions of Markov chains
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Publication:1167473
DOI10.1016/0304-4149(83)90047-9zbMath0491.60028OpenAlexW2030462712MaRDI QIDQ1167473
Publication date: 1983
Published in: Stochastic Processes and their Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0304-4149(83)90047-9
Infinitely divisible distributions; stable distributions (60E07) Central limit and other weak theorems (60F05) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)
Related Items (10)
Rigorous statistical procedures for data from dynamical systems ⋮ Markov Extensions, Zeta Functions, and Fredholm Theory for Piecewise Invertible Dynamical Systems ⋮ Moment inequalities for mixing sequences of random variables ⋮ Estimating beta-mixing coefficients via histograms ⋮ Convergence of changepoint estimators for weakly dependent data ⋮ On a very weak bernoulli condition† ⋮ A note on uniform laws of averages for dependent processes ⋮ Periodicity and absolute regularity ⋮ Asymptotic properties for l 1 norm kernel estimator of conditional median under dependence ⋮ Some mixing properties of time series models
Cites Work
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- On the \(\varphi\)-mixing condition for stationary random sequences
- On isomorphism of weak Bernoulli transformations
- Some Limit Theorems for Random Functions. I
- On the ψ-Mixing Condition for Stationary Random Sequences
- Some Limit Theorems for Random Functions. II
- Mixing Conditions for Markov Chains
- Limiting behavior of U-statistics for stationary, absolutely regular processes
- Limiting behavior of one-sample rank-order statistics for absolutely regular processes
- A partition on a Bernoulli shift which is not weakly Bernoulli
- Some Limit Theorems for Stationary Processes
- On a Class of Markov Processes
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