Additive inverse regression models with convolution-type operators
From MaRDI portal
Publication:2441045
DOI10.1214/13-EJS874zbMath1348.62135arXiv1303.4179MaRDI QIDQ2441045
Nicolai Bissantz, Thimo Hildebrandt, Dette, Holger
Publication date: 21 March 2014
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1303.4179
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric tolerance and confidence regions (62G15)
Related Items (3)
Smooth backfitting in additive inverse regression ⋮ Wavelet Estimation for Regression Convolution Model with Heteroscedastic Errors ⋮ Semi‐parametric Estimation in a Single‐index Model with Endogenous Variables
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The existence and asymptotic properties of a backfitting projection algorithm under weak conditions
- Backfitting and smooth backfitting for additive quantile models
- On the optimal rates of convergence for nonparametric deconvolution problems
- Estimation of additive quantile regression
- Asymptotic normality and confidence intervals for inverse regression models with convolution-type operators
- On spline estimators and prediction intervals in nonparametric regression.
- Statistical and computational inverse problems.
- Sharp adaptation for inverse problems with random noise
- Rate optimal estimation with the integration method in the presence of many covariates
- Confidence bands for inverse regression models
- Deconvolving kernel density estimators
- Nonparametric statistical inverse problems
- Image deblurring with Poisson data: from cells to galaxies
- On Additive Conditional Quantiles With High-Dimensional Covariates
- Smooth Backfitting in Practice
- Statistical Inverse Estimation in Hilbert Scales
- ESTIMATION IN AN ADDITIVE MODEL WHEN THE COMPONENTS ARE LINKED PARAMETRICALLY
- A kernel method of estimating structured nonparametric regression based on marginal integration
- Convergence Rates of General Regularization Methods for Statistical Inverse Problems and Applications
- Nonparametric Estimation of an Additive Quantile Regression Model
- Time Series
This page was built for publication: Additive inverse regression models with convolution-type operators