Efficient Penalized Estimation for Linear Regression Model
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Publication:5265841
DOI10.1080/03610926.2012.763094zbMath1328.62460OpenAlexW2053340105MaRDI QIDQ5265841
Publication date: 29 July 2015
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2012.763094
Applications of statistics to economics (62P20) Ridge regression; shrinkage estimators (Lasso) (62J07)
Cites Work
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- Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
- One-step sparse estimates in nonconcave penalized likelihood models
- Estimating the dimension of a model
- Heuristics of instability and stabilization in model selection
- Asymptotics for Lasso-type estimators.
- Least angle regression. (With discussion)
- On the adaptive elastic net with a diverging number of parameters
- A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
- An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator
- Automatic Lag Selection in Covariance Matrix Estimation
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Regularization Parameter Selections via Generalized Information Criterion
- Nonconcave Penalized Likelihood With NP-Dimensionality
- Regularization and Variable Selection Via the Elastic Net
- Tuning parameter selectors for the smoothly clipped absolute deviation method
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