Robust and efficient estimation of nonparametric generalized linear models

Cites Work

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Robust estimation for independent non-homogeneous observations using density power divergence with applications to linear regression
A statistical perspective on ill-posed inverse problems (with discussion)
Robust estimation for nonparametric generalized regression
\(M\)-type penalized splines with auxiliary scale estimation
Composite quantile regression and the oracle model selection theory
Robust estimation of error scale in nonparametric regression models
On a robust local estimator for the scale function in heteroscedastic nonparametric regression
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Penalized quasi-likelihood estimation in partial linear models
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Asymptotic theory of penalized splines
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Asymptotic analysis of penalized likelihood and related estimators
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An Outlier-Robust Fit for Generalized Additive Models With Applications to Disease Outbreak Detection
Asymptotic properties of penalized spline estimators
Model Selection and Model Averaging
Robust Locally Weighted Regression and Smoothing Scatterplots
Robust and efficient estimation by minimising a density power divergence
Asymptotic Statistics
Semiparametric Regression
Robust Inference for Generalized Linear Models
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Robust Statistics
Smoothing Spline Gaussian Regression: More Scalable Computation via Efficient Approximation
Robust estimation for non-homogeneous data and the selection of the optimal tuning parameter: the density power divergence approach
Choosing a robustness tuning parameter
Robust Variable Selection With Exponential Squared Loss
On the ‘optimal’ density power divergence tuning parameter
Robust Statistics
A practical guide to splines.