http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Ryeji Jeong(정례지) (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
On the robustification of the z-test statistic
Ryeji Jeong(정례지),Seung Bin Son(손승빈),Hee Joo Lee(이희주),Haewon Kim(김해원) 대한산업공학회 2018 대한산업공학회 춘계학술대회논문집 Vol.2018 No.4
The z-test statistic is one of the most popular statistics. However, this conventional z-test has a serious pitfall when some of observations in a sample are contaminated. We propose two alternatives which satisfy asymptotic normality. We used the median or Hodges-Lehmann estimator instead of the mean and we also used the median absolute deviation or Shamos estimator instead of the standard deviation in the z-test statistic. The proposed alternatives are easy to implement. Thus, it is quite useful for engineers and practitioners. Through extensive Monte Carlo simulations, we obtained the empirical statistical power curves which clearly show that the proposed alternatives outperform the traditional method based on the z-test. A real-data illustration is also provided.
-
On the robustification of the z-test statistic
Ryeji Jeong(정례지),Seung Bin Son(손승빈),Hee Joo Lee(이희주),Haewon Kim(김해원) 한국경영과학회 2018 한국경영과학회 학술대회논문집 Vol.2018 No.04
The z-test statistic is one of the most popular statistics. However, this conventional z-test has a serious pitfall when some of observations in a sample are contaminated. We propose two alternatives which satisfy asymptotic normality. We used the median or Hodges-Lehmann estimator instead of the mean and we also used the median absolute deviation or Shamos estimator instead of the standard deviation in the z-test statistic. The proposed alternatives are easy to implement. Thus, it is quite useful for engineers and practitioners. Through extensive Monte Carlo simulations, we obtained the empirical statistical power curves which clearly show that the proposed alternatives outperform the traditional method based on the z-test. A real-data illustration is also provided.
-
Hyper Parameter Tuning Method based on Sampling for Optimal LSTM Model
Hyemee Kim(김혜미),Ryeji Jeong(정례지),Hyerim Bae(배혜림) 한국컴퓨터정보학회 2019 韓國컴퓨터情報學會論文誌 Vol.24 No.1
As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.
ScienceON연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
