Complete moment convergence for the dependent linear processes with random coefficients
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Publication:2273236
DOI10.1007/s10114-019-8205-zzbMath1420.60041OpenAlexW2944230028WikidataQ127941690 ScholiaQ127941690MaRDI QIDQ2273236
Publication date: 18 September 2019
Published in: Acta Mathematica Sinica. English Series (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10114-019-8205-z
random coefficientslinear processescomplete moment convergenceextended negatively dependent random variables
Related Items (8)
Complete moment convergence for the linear processes with random coefficients generated by a class of random variables ⋮ Complete moment convergence for the widely orthant dependent linear processes with random coefficients ⋮ Limiting behaviors of linear processes with random coefficients based on m-ANA random variables ⋮ Complete $f$-Moment Convergence for Randomly Weighted Sums of Extended Negatively Dependent Random Variables and Its Statistical Application ⋮ A general result on complete f -moment convergence with its application to nonparametric regression models ⋮ Complete f -moment convergence for weighted sums of asymptotically almost negatively associated random variables and its application in semiparametric regression models ⋮ Complete convergence for weighted sums of widely orthant-dependent random variables and its statistical application ⋮ Complete Moment Convergence for the Dependent Linear Processes with Application to the State Observers of Linear-Time-Invariant Systems
Cites Work
- Unnamed Item
- Complete moment convergence for product sums of sequence of extended negatively dependent random variables
- Central limit theorem for stationary linear processes generated by linearly negative quadrant-dependent sequence
- Complete \(q\)th moment convergence for arrays of random variables
- On complete convergence of moving average process for AANA sequence
- Complete convergence of weighted sums for arrays of rowwise \(\varphi \)-mixing random variables.
- Complete moment convergence of moving average processes under dependence assumptions
- Necessary and sufficient conditions for moderate deviations of dependent random variables with heavy tails
- Moment inequalities and complete moment convergence
- Asymptotics for linear processes
- A maximal inequality and dependent strong laws
- The convergence of double-indexed weighted sums of martingale differences and its application
- Strong laws of large numbers for weighted sums of random elements in normed linear spaces
- Precise large deviations for random sums of END real-valued random variables with consistent variation
- Complete moment convergence of moving average processes under \(\varphi \)-mixing assumptions
- A note on complete convergence of weighted sums for array of rowwise AANA random variables
- Complete moment convergence for i.i.d. random variables
- Complete convergence for weighted sums of END random variables and its application to nonparametric regression models
- Equivalent Conditions of Complete Moment Convergence of Weighted Sums for ϕ-Mixing Sequence of Random Variables
- Convergence of Moving Average Processes for Dependent Random Variables
- ON THE COMPLETE MOMENT CONVERGENCE OF MOVING AVERAGE PROCESSES GENERATED BY ρ*-MIXING SEQUENCES
- STRONG LAWS OF LARGE NUMBERS FOR LINEAR PROCESSES GENERATED BY ASSOCIATED RANDOM VARIABLES IN A HILBERT SPACE
- COMPLETE MOMENT CONVERGENCE OF MOVING AVERAGE PROCESSES WITH DEPENDENT INNOVATIONS
- Some general strong laws for weighted sums of stochastically dominated random variables
- Invariance principles for dependent variables
- Complete moment convergence forweighted sums of extended negatively dependent random variables
- Convergence rates in the law of large numbers for END linear processes with random coefficients
- Complete consistency for the estimator of nonparametric regression models based on extended negatively dependent errors
- Complete moment convergence of pairwise NQD random variables
- Complete qth moment convergence of weighted sums for arrays of rowwise negatively associated random variables
- Limit Theorems for Moving Averages with Random Coefficients and Heavy-Tailed Noise
- Some Concepts of Dependence
- Marcinkiewicz-Zygmund strong laws for infinite variance time series.
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