Asymptotic normality for the wavelets estimator of the additive regression components

DOI10.1016/j.crma.2006.10.003zbMath1101.62038OpenAlexW2056748803MaRDI QIDQ857121

Mohammed Debbarh

Publication date: 14 December 2006

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.crma.2006.10.003

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Central limit and other weak theorems (60F05)

Related Items

Adaptive estimation of an additive regression function from weakly dependent data, Some asymptotic properties of kernel regression estimators of the mode for stationary and ergodic continuous time processes

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Additive regression and other nonparametric models
• Density estimation in Besov spaces
• Mixing: Properties and examples
• Multivariate probability density estimation by wavelet methods: Strong consistency and rates for stationary time series
• Wavelets, approximation, and statistical applications
• Wavelet threshold estimation for additive regression models
• Adaptive confidence interval for pointwise curve estimation.
• Additive time series: The kernel integration method
• Wavelet linear density estimator for a discrete-time stochastic process: \(L_ p\)-losses
• Recursive probability density estimation for weakly dependent stationary processes
• Wavelet Methods for Curve Estimation
• NONPARAMETRIC ESTIMATION AND TESTING OF INTERACTION IN ADDITIVE MODELS
• Some Limit Theorems for Stationary Processes