Pointwise wavelet change-points estimation for dependent biased sample

DOI10.1016/j.cam.2020.112986zbMath1441.62096OpenAlexW3029498584MaRDI QIDQ2186933

Xinsheng Liu, Yuncai Yu

Publication date: 10 June 2020

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2020.112986

zbMATH Keywords

pointwise estimationmultiple change-pointsjump sizesblock thresholding waveletdependent biased sample

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40)

Related Items (2)

Wavelet change-point estimation for the density based on biased sample ⋮ Pointwise wavelet estimation of density function with change-points based on NA and biased sample

Uses Software

• WaveThresh4
• rwavelet

Cites Work

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• On minimaxity of block thresholded wavelets under elliptical symmetry
• Generalized kernel regression estimator for dependent size-biased data
• On multivariate kernel estimation for samples from weighted distributions
• A connection between supermodular ordering and positive/negative association.
• Adaptive wavelet estimation: A block thresholding and oracle inequality approach
• Asymptotic normality of a wavelet estimator for asymptotically negatively associated errors
• Detection of multiple change points for linear processes under negatively super-additive dependence
• Pointwise density estimation for biased sample
• Strong and weak consistency of LS estimators in the EV regression model with negatively superadditive-dependent errors
• Complete convergence for weighted sums of NSD random variables and its application in the EV regression model
• Wavelet estimation of a regression function with a sharp change point in a random design
• M-test in linear models with negatively superadditive dependent errors
• On the minimax optimality of block thresholded wavelet estimators with long memory data
• Nonparametric Wavelet Regression Based on Biased Data
• Non parametric regression estimations over L^p risk based on biased data
• Wavelet change-point estimation for long memory non-parametric random design models
• Jump and sharp cusp detection by wavelets
• Kernel regression in the presence of size-bias
• Detection and Estimation of Jump Points in Non parametric Regression Function withAR(1) Noise
• Wavelet-based estimation of regression function for dependent biased data under a given random design

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