| 二元选择分位回归的自适应LASSO改进 |
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| 引用本文：李楚进，张翠霞.二元选择分位回归的自适应LASSO改进[J].经济数学,2018,(2):89-97 |
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| 中文摘要:为避免模型出现过拟合，将自适应LASSO变量选择方法引入二元选择分位回归模型，利用贝叶斯方法构建Gibbs抽样算法并在抽样中设置不影响预测结果的约束条件‖β‖=1以提高抽样值的稳定性.通过数值模拟，表明改进的模型有更为良好的参数估计效率、变量选择功能和分类能力. |
| 中文关键词:应用统计数学；分位回归；自适应LASSO 变量选择；二元选择模型 |
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| Improvement of Binary Quantile Regression Based on Adaptive LASSO |
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| Abstract:Binary quantile regression model with the adaptive LASSO penalty is proposed for overfitting problems by presenting a Bayesian Gibbs sampling algorithm to estimate parameters. In the process of sampling, the restriction on ‖β‖=1 is motivated to improve the stability of the sampling values. Numerical analysis show there are better improvements of the proposed method in parameter estimation, variable selection and classification. |
| keywords:applied statistics & mathematics quantile regression adaptive LASSO variable selection binary regression |
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