Sampling properties of \(U\)-statistics for a class of stationary nonlinear processes
From MaRDI portal
Publication:853838
DOI10.1007/s10463-006-0030-3zbMath1100.62051OpenAlexW2007832950MaRDI QIDQ853838
Publication date: 17 November 2006
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-006-0030-3
Asymptotic properties of nonparametric inference (62G20) Sampling theory, sample surveys (62D05) Stationary stochastic processes (60G10) Inference from stochastic processes (62M99)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Approximation theorems for strongly mixing random variables
- Some mixing properties of time series models
- Current developments in time series modelling
- Mixing: Properties and examples
- Density estimation for a class of stationary nonlinear processes
- A central limit theorem for m-dependent random variables with unbounded m
- The central limit theorem for dependent random variables
- Limit theorems for functionals of mixing processes with applications to $U$-statistics and dimension estimation
- A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
- On U-statistics and v. mise? statistics for weakly dependent processes
- Linear processes and bispectra
- Central Limit Theorems for dependent variables. I
- STATIONARITY AND CENTRAL LIMIT THEOREM ASSOCIATED WITH BILINEAR TIME SERIES MODELS
- Limiting behavior of U-statistics for stationary, absolutely regular processes
- Probability inequalities for sums of absolutely regular processes and their applications
- On the Strong Mixing Property for Linear Sequences
- Strong mixing properties of linear stochastic processes
- Convergence of Distributions Generated by Stationary Stochastic Processes
- Limiting behavior of regular functionals of empirical distributions for stationary *-mixing processes
- Functional central limit theorems for strictly stationary processes satisfying the strong mixing condition
- Some Limit Theorems for Stationary Processes
- A Class of Statistics with Asymptotically Normal Distribution
This page was built for publication: Sampling properties of \(U\)-statistics for a class of stationary nonlinear processes
