Model selection in regression based on pre-smoothing
From MaRDI portal
Publication:5123630
DOI10.1080/02664760903046086OpenAlexW2144605927WikidataQ56880813 ScholiaQ56880813MaRDI QIDQ5123630
Niel Hens, Jeffrey S. Simonoff, Marc Aerts
Publication date: 29 September 2020
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: http://archive.nyu.edu/handle/2451/26303
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A class of linear regression parameter estimators constructed by nonparametric estimation
- Estimating the dimension of a model
- A method for simultaneous variable selection and outlier identification in linear regression
- Nonparametric regression with correlated errors.
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- The problem of regions
- Smoothing methods in statistics
- Akaike's Information Criterion in Generalized Estimating Equations
- Model Selection in Estimating Equations
- Minimizing GCV/GML Scores with Multiple Smoothing Parameters via the Newton Method
- Simultaneous variable selection and outlier identification in linear regression using the mean-shift outlier model
- On Measuring and Correcting the Effects of Data Mining and Model Selection
- Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
- Semiparametric Regression
- EFFICIENCY OF LINEAR REGRESSION ESTIMATORS BASED ON PRESMOOTHING
- Model Selection and Multimodel Inference
- Bayesian Measures of Model Complexity and Fit