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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.5
- 수록면
- 517 - 531 (15page)
- DOI
- 10.7465/jkdi.2022.33.3.517
이용수
초록· 키워드
오류제보하기
We consider a nonparametric function estimation method with mixed degree using weighted lasso penalty. The ℓ₁ norm penalty controls linear and cubic trends depending on the value of the parameter. In the proposed estimator, we introduce one computational algorithm for constrained convex optimization problems corresponding to the Lagrangian dual problem based on quadratic programming. Subsequently, using simulations and two real data analyses, numerical studies are conducted to verify the performance of the estimator of the proposed method by identifying the relationship between the data.
목차
Abstract
1. Introduction
2. Model and Estimator
3. Implementation
4. Numerical analysis
5. Conclusion
References
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UCI(KEPA) : I410-ECN-0101-2022-041-001346695