Asymptotic distribution of the wavelet-based estimators of multivariate regression functions under weak dependence

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Nonparametric statistical resampling methods (62G09)

Cites Work

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Multivariate wavelet density and regression estimators for stationary and ergodic continuous time processes: asymptotic results
A simple bootstrap method for constructing nonparametric confidence bands for functions
A note on the adaptive estimation of a conditional continuous-discrete multivariate density by wavelet methods
Uniform limit theorems for wavelet density estimators
Nonlinear wavelet density estimation with data missing at random when covariates are present
Maximum penalized likelihood estimation. Volume II: Regression
On the invariance principle for sums of independent identically distributed random variables
A new mixing notion and functional central limit theorems for a sieve bootstrap in time series
Probability density estimation from dependent observations using wavelets orthonormal bases
Multivariate probability density estimation by wavelet methods: Strong consistency and rates for stationary time series
Wavelets, approximation, and statistical applications
A new weak dependence condition and applications to moment inequalities
Stochastic models for time series
Density estimation by wavelet thresholding
A distribution-free theory of nonparametric regression
Some remarks on coupling of dependent random variables
Asymptotic theory of weakly dependent stochastic processes
Uniform consistency and uniform in number of neighbors consistency for nonparametric regression estimates and conditional \(U\)-statistics involving functional data
Uniform convergence rates for wavelet curve estimation in sup-norm loss
Some asymptotic properties of kernel regression estimators of the mode for stationary and ergodic continuous time processes
A new covariance inequality and applications.
Weak dependence. With examples and applications.
An approximation to the density function
Functional Estimation of a Density Under a New Weak Dependence Condition
Multivariate wavelet density and regression estimators for stationary and ergodic discrete time processes: Asymptotic results
A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
Non-strong mixing autoregressive processes
Convergence rates for density estimators of weakly dependent time series
Mathematical Foundations of Infinite-Dimensional Statistical Models
Ten Lectures on Wavelets
Wavelet-Based estimation of multivariate regression functions in besov spaces^*
Adaptive wavelet estimation of a function from an m-dependent process with possibly unbounded m
Some results about kernel estimators for function derivatives based on stationary and ergodic continuous time processes with applications
Uniform consistency and uniform in bandwidth consistency for nonparametric regression estimates and conditional U-statistics involving functional data
Multivariate Density Estimation
All of Nonparametric Statistics
On Estimation of a Probability Density Function and Mode
Combinatorial methods in density estimation
Cross-validation for choosing resolution level for nonlinear wavelet curve estimators
Uniform in bandwidth consistency of conditional \(U\)-statistics adaptive to intrinsic dimension in presence of censored data

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