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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국통계학회 CSAM(Communications for Statistical Applications and Methods) CSAM(Communications for Statistical Applications and Methods) 제28권 제4호
- 발행연도
- 2021.7
- 수록면
- 351 - 368 (18page)
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초록· 키워드
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For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen’s estimator (Shen et al., 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ<SUP>2</SUP>. The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen’s estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen’s estimator when σ<SUP>2</SUP> is small and exhibits a meaningful decrease in the RMSE under moderate and large σ<SUP>2</SUP> values.
목차
Abstract
1. Introduction
2. Existing estimators
3. Proposed estimator
4. Numerical study for risk comparison
5. Conclusion
References
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