Regularization parameter selection in indirect regression by residual based bootstrap
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Publication:5134476
DOI10.5705/ss.202018.0160zbMath1453.62389arXiv1610.08663OpenAlexW2963116437MaRDI QIDQ5134476
Nicolai Bissantz, Justin Chown, Dette, Holger
Publication date: 16 November 2020
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1610.08663
regularizationinverse problemsbandwidth selectionsmooth bootstrapindirect regression estimatorresidual-based empirical distribution function
Bootstrap, jackknife and other resampling methods (62F40) Statistical ranking and selection procedures (62F07)
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Cites Work
- Unnamed Item
- Locally adaptive image denoising by a statistical multiresolution criterion
- Risk hull method and regularization by projections of ill-posed inverse problems
- On the optimal rates of convergence for nonparametric deconvolution problems
- The choice of smoothing parameter in nonparametric regression through wild bootstrap
- Multivariate density estimation with general flat-top kernels of infinite order
- Estimating linear functionals of the error distribution in nonparametric regression
- Sharp adaptation for inverse problems with random noise
- On pointwise adaptive nonparametric deconvolution
- General regularization schemes for signal detection in inverse problems
- Confidence bands for multivariate and time dependent inverse regression models
- Bootstrapping the mean integrated squared error
- Confidence bands for inverse regression models
- Discrepancy principle for statistical inverse problems with application to conjugate gradient iteration
- Multivariate probability density deconvolution for stationary random processes
- Regularization of some linear ill-posed problems with discretized random noisy data
- Nonparametric statistical inverse problems
- Statistical inference for inverse problems
- Approximating data with weighted smoothing splines
- Smooth Residual Bootstrap for Empirical Processes of Non‐parametric Regression Residuals
- Optimal Adaptation for Early Stopping in Statistical Inverse Problems
- Statistical Inverse Estimation in Hilbert Scales
- Adaptive hard-thresholding for linear inverse problems
- Estimating the error distribution function in semiparametric regression
- On the Estimation of the Probability Density, I
- On Estimation of a Probability Density Function and Mode
- Introduction to nonparametric estimation
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