• Journal of the Korean Statistical Society
• /
• 제26권2호
• /
• pp.245-259
• /
• 1997

The paper shows that certain hierachical Bayes (HB) predictors for small domain data in repeated surveys "universally" or "stochastically" dominate all linear unbiased predictors. Also, the HB predictors are "best" within the class of all equivariant predictors under a certain group of transformations.tain group of transformations.

• 한방비만학회지
• /
• 제18권2호
• /
• pp.115-127
• /
• 2018

Objectives: People often fail to reduce or maintain their weight despite trying to lose weight. The purpose of this study was to review previously published study results of the predictive factors associated with weight loss in obesity treatment. Methods: Authors searched for the articles related to weight loss, published from 2007 to 2017 found on PubMed, Scopus, Research Information Sharing Service (RISS), and Koreanstudies Information Service System (KISS). A total of 43 articles were finally selected. From the study results, unchangeable and changeable predictors were extracted, and these predictors were examined according to detailed categories. Results: Predictors of weight loss in obesity treatment included genetic and physiological factors, demographic factors, history of treatment on obesity related factors, behavioral factors, psychological factors and treatment process related factors. The main factors of weight loss were unchangeable predictors such as high initial degree of obesity and younger age, and changeable predictors such as dietary restraint, regular exercise, self-efficacy, initial weight loss and attendance. Especially dietary restraint, regular exercise, successful initial weight loss and high attendance were considered to be dominant factors for weight loss treatments. Conclusions: Our review results suggest that unchangeable and changeable predictors of weight loss should be carefully examined during treatments of obesity.

• 한국의류학회지
• /
• 제12권3호
• /
• pp.295-307
• /
• 1988

The purposes of the study were to identify the general predictors of fashion leadership and to compare the fashion leadership predictors among different social groups. Thirty-one variables (thirteen fashion-related variables, five social variables, nine psychological variables, four demographic variables) were included in the regression analysis. Data were obtained from 446 women living in Seoul area by self-administered questionnaire. The results of the study were as follows: 1. Seven variables explained about 64 percent of the total variance of fashion leadership. The most important predictors of fashion leadership were fashion interest, use of marketer-dominated fashion information source, and 'stable-creative' self-image. 2. The predictors that consistently predict fashion leadership across different social groups (students, career women, housewives) were fashion interest and use of marketer-dominated information source. The predictors of innovativeness and opinion leadership were very different among groups.

• 대한한의학회지
• /
• 제37권3호
• /
• pp.62-73
• /
• 2016

Objectives: Dropout and weight regain are common problems in most obesity treatments. The purpose of this study was to review previously published study results of the predictive factors associated with dropout during weight loss treatment and weight loss maintenance after successful weight loss. Methods: Authors searched for the articles related to dropout and weight loss maintenance, published from 2007 to 2016 found on Pubmed, Scopus, RISS, and KISS. A total of 19 articles were finally selected. From the study results, unchangeable and changeable predictors were extracted, and these predictors were examined according to dropout and weight loss maintenance categories. Results: The unchangeable predictors of dropout were younger age, lower education level and female, whereas the changeable predictors of dropout were lower initial weight loss, symptoms of depression and body dissatisfaction. The strongest factor for predicting the dropout was initial weight loss. The unchangeable predictors of weight loss maintenance were old age, male and family history of obesity, whereas the changeable predictors of weight loss maintenance were regular exercise, dietary restraint, self-weighing and low depressive symptoms. Initial weight loss, depressive symptoms, body image, dietary restraint, physical activity, weight loss expectation and social support were considered to be dominant factors for weight loss treatments. Conclusions: Our review results suggest that unchangeable and changeable predictors of dropout and weight loss maintenance should be carefully examined during treatments of obesity.

• 한방비만학회지
• /
• 제19권2호
• /
• pp.119-136
• /
• 2019

Objectives: People often fail to maintain their weight even though they have succeeded in weight loss. The purpose of this study was to review previously published study results with regards to the predictive factors associated with weight loss maintenance after successful weight loss. Methods: The authors searched for the articles related to weight loss maintenance after successful weight loss, published up until June 2019 on PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Research Information Sharing Service (RISS), and Koreanstudies Information Service System (KISS). A total of 76 articles were finally selected. From the study results, changeable and unchangeable predictors were extracted, and these predictors were examined according to detailed categories. Results: The changeable predictors of weight loss maintenance included behavioral factors, psychological factors and treatment process-related factors, whereas the unchangeable predictors included genetic and physiological factors, demographic factors, history of treatment on obesity-related factors. The main factors of weight loss maintenance were changeable predictors such as healthy eating habits, dietary intake control, binge eating control, regular exercise and physical activity, depression and stress control, social supports, self-regulation, self-weighing and initial weight loss and unchangeable predictors such as low initial weight and maximum lifetime weight. Conclusions: The results of our review results suggest that changeable and unchangeable predictors of weight loss maintenance should be carefully examined during treatments of obesity.

• 지능정보연구
• /
• 제13권2호
• /
• pp.15-26
• /
• 2007

본 연구에서는 기존 Bagging Predictors에 수정을 가한 Modified Bagging Predictors를 이용하여 SOHO에 대한 부도예측 모델을 제시한다. 대기업 및 중소기업에 대한 기업부도예측 모델에 대한 많은 선행 연구가 있어왔지만 SOHO만의 기업부도 예측 모델에 관한 연구는 미비한 상태이다. 금융기관들의 대출 심사 시 대기업 및 중소기업과는 달리 SOHO에 대한 대출심사는 아직은 체계화되지 못한 채 신용정보점수 등의 단편적인 요소를 사용하고 있는 것이 현실이고 이에 따라 잘못된 대출로 인한 금융기관의 부실화를 초래할 위험성이 크다. 본 연구에서는 실제국내은행의 SOHO 대출 데이터 집합이 사용되었다. 먼저, 기업부도 예측 모델에서 우수하다고 연구되어진 인공신경망과 의사결정나무 추론 기법을 적용하여 보았지만 만족할 만한 성과를 이끌어내지 못하여, 기존 기업부도 예측 모델 연구에서 적용이 미비하였던 Bagging Predictors와 이를 개선한 Modified Bagging Predictors를 제시하고 이를 적용하여 보았다. 연구결과, SOHO 부도 예측에 있어서 본 연구에서 제시한 Modified Bagging Predictors가 인공신경망과 Bagging Predictors 등의 기존 기법에 비해서 성과가 향상됨을 알 수 있었다.

• 한국환경과학회지
• /
• 제22권8호
• /
• pp.953-963
• /
• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• 응용통계연구
• /
• 제23권5호
• /
• pp.977-985
• /
• 2010

In this paper, we propose an approach to conduct partial sufficient dimension reduction with heavily unbalanced categorical predictors. For this, we consider integrated categorical predictors and investigate certain conditions that the integrated categorical predictor is fully informative to partial sufficient dimension reduction. For illustration, the proposed approach is implemented on optimal partial sliced inverse regression in simulation and data analysis.

• 정보처리학회논문지A
• /
• 제9A권4호
• /
• pp.497-502
• /
• 2002

조건부 분기 명령어는 분기 벌칙을 야기함으로써 명령어 수준의 병렬도 향상에 제약을 가한다. 고성능 슈퍼스칼라 프로세서의 등장으로 인해, 정확한 분기 예측의 중요성은 더욱 높아지고, 이를 위해 동적 분기 예측의 일종인 2단계 적응적 분기 예측(2-level adaptive branch prediction) 방식이 개발되었다. 그러나 2단계 적응적 분기 예측이 상당히 높은 예측 정확도를 보여주고 있음에도 불구하고, 정확도에 따른 비용이 기하급수적으로 증가하는 등의 문제점을 가지고 있다. 본 논문에서는 2단계 적응적 분기 예측의 이러한 문제점을 개선하기 위하여 세트 연관 캐쉬를 이용한 캐쉬 상관 분기 예측기(cached correlated branch predictor)를 제안하고, 기존의 방식에 비해 예측의 정확도는 증가하고, 비용은 줄어든 것을 시뮬레이션을 통하여 확인한다. 세트 연관 예측기의 경우 전역과 지역 방식의 가장 좋은 예측 실패율은 각각 5.99%, 6.28%이며, 이는 종래의 2단계 적응적 분기 예측 방식에서의 가장 좋은 결과인 9.23%, 7.35%에 비해 각각 54%, 17% 향상된 결과이다.

• 대한간호학회지
• /
• 제37권4호
• /
• pp.459-466
• /
• 2007

Purpose: This study was to identify predictors of quality of life in breast cancer patients. Physical and pscyhological factors like stress, mood, and fatigue with sociodemographic factors like education, income, job and stage of disease were used to predict quality of life. Methods: One hundred eleven patients with breast cancer participated in this study? The functional Assessment of Cancer Therapy-Breast(FACT-B) was used to assess quality of life. Results: The mean age of the patients was 46.7 years. The FACT-B mean score was 89.89(SD:17.31) Education, income, job and stage of disease were significantly associated with QOL. In a regression analysis, mood, income, and fatigue were significant predictors for QOL where as, stress was not significant. Among the subscales of QOL, physical well-being, functional well-being, emotional well-being, and the breast cancer subscale were included as predictors of QOL Conclusion: Physical and psychological factors were strong predictors of QOL. These results demonstrate the need for interventions to improve QOL in breast cancer survivors.