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De-noising boosting methods for variable selection and estimation subject to error-prone variables.

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Title: De-noising boosting methods for variable selection and estimation subject to error-prone variables.
Authors: Chen, Li-Pang1 (AUTHOR) lchen723@nccu.edu.tw
Source: Statistics & Computing. Apr2023, Vol. 33 Issue 2, p1-13. 13p.
Database: Mathematics Source
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  Data: De-noising boosting methods for variable selection and estimation subject to error-prone variables.
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        Value: 10.1007/s11222-023-10209-3
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              Text: Apr2023
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