Nonparametric estimation for dependent data
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Publication:3106417
DOI10.1080/10485252.2010.484491zbMath1228.62046OpenAlexW2011005963MaRDI QIDQ3106417
Jan Johannes, Suhasini Subba Rao
Publication date: 21 December 2011
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485252.2010.484491
Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09)
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Change point detection for nonparametric regression under strongly mixing process ⋮ Generalized Birnbaum-Saunders kernel density estimators and an analysis of financial data ⋮ Donsker results for the empirical process indexed by functions of locally bounded variation and applications to the smoothed empirical process
Cites Work
- Unnamed Item
- Unnamed Item
- Mixing properties of ARCH and time-varying ARCH processes
- Nonparametric regression with long-range dependence
- Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression
- Convergence rates in density estimation for data from infinite-order moving average processes
- Asymptotic normality of regression estimators with long memory errors
- Quadratic errors for nonparametric estimates under dependence
- Nonparametric statistics for stochastic processes. Estimation and prediction.
- Random-design regression under long-range dependent errors
- Mixing: Properties and examples
- Semiparametric estimation from time series with long-range dependence
- A covariance inequality under a two-part dependence assumption
- On the asymptotic mean integrated squared error of a kernel density estimator for dependent data
- Regular variation of GARCH processes.
- The mixing property of bilinear and generalised random coefficient autoregressive models
- Effect of dependence on stochastic measures of accuracy of density estimators
- Nonparametric regression under long-range dependent normal errors
- Log-periodogram regression of time series with long range dependence
- On bandwidth choice for density estimation with dependent data
- About the Lindeberg method for strongly mixing sequences
- THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
- NONPARAMETRIC ESTIMATORS FOR TIME SERIES
- Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
- Mixing properties of harris chains and autoregressive processes
- Root-N-Consistent Semiparametric Regression
- On the Strong Mixing Property for Linear Sequences
- Stochastic Limit Theory
- Nonparametric estimation under long memory dependence
- Strong mixing properties of linear stochastic processes
- LONG-RANGE DEPENDENCE AND MIXING FOR DISCRETE TIME FRACTIONAL PROCESSES
- STATIONARY ARCH MODELS: DEPENDENCE STRUCTURE AND CENTRAL LIMIT THEOREM
- Estimating Semiparametric ARCH(oo) Models by Kernel Smoothing Methods1
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