Robust variable selection with exponential squared loss for the spatial autoregressive model
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Publication:829731
DOI10.1016/J.CSDA.2020.107094OpenAlexW3089507321WikidataQ115577947 ScholiaQ115577947MaRDI QIDQ829731
Lu Lin, Yunquan Song, Yanji Zhu, Xi-Jun Liang
Publication date: 6 May 2021
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2020.107094
Related Items (4)
Exponential squared loss based robust variable selection of AR models ⋮ Robust transfer learning of high-dimensional generalized linear model ⋮ Robust variable selection with exponential squared loss for partially linear spatial autoregressive models ⋮ Robust empirical likelihood inference for partially linear varying coefficient models with longitudinal data
Uses Software
Cites Work
- The Adaptive Lasso and Its Oracle Properties
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Composite quantile regression and the oracle model selection theory
- Hedonic housing prices and the demand for clean air
- Spatial weights matrix selection and model averaging for spatial autoregressive models
- Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
- Approximations of the critical region of the fbietkan statistic
- Regression Quantiles
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- A Naive Least Squares Method for Spatial Autoregression with Covariates
- Robust estimation for functional coefficient regression models with spatial data
- Variable Selection for Partially Linear Models With Measurement Errors
- Robust Variable Selection With Exponential Squared Loss
- Robust Statistics
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