• Title/Summary/Keyword: Principal Component Factor Analysis

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Comparison of Dietary Externalization in Korea and Japan -by Principal Component Analysis- (식생활 외부화에 관한 한일 비교 연구 -주성분 분석을 이용하여-)

  • Choi Hyun-Sook
    • Journal of the East Asian Society of Dietary Life
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    • v.16 no.1
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    • pp.23-28
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    • 2006
  • The purpose of this paper was to clarify the actual conditions of the 'Dietary externalization' mainly by using the economic and nutrition-related data, accompanied by the economic development in Korea and Japan. 'Modernization of food style' and other modernization have taken place, among which 'Dietary externalization' in particular has recently drawn interest. At the time this paper clarified with econometric analysis whether there are differences between the two countries in term of the modernization of food style and dietary externalization trend. The trends of Dietary externalization of both Korea and Japan were studied using Principal Component Analysis method. The food subgroup were investigated based on the annual report on the household income and expenditure survey of Korea and the annual report on the family income and expenditure survey of Japan. The statistical data from both country were analyzed by SAS program. The results are as follows; 1. In Korea, the ratio of carbohydrates in the total calorie intake is quite high and animal protein is rather low compared to those in Japan. 2. Traditional food such as grains and vegetables are consumed much more in Korea than in Japan. 3. The Principal Component 1, 2 were extracted in both countries during the whole analysis period, which suggested the 'Dietary externalization' 4. Principal Component 1 has a positive factor loaded in all food items including meals outside the home and process food. In other words, it is apparent that the 'Dietary externalization' tread in Korea has a simple pattern suggesting that all externalization related items are on the rise. 5. Principal component 1, 2 which indicated the dietary externalization, were detected in Japan.

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Watershed Classification Using Statistical Analysis of water Quality Data from Muju area (무주지역 수질특성자료의 통계학적 분석에 의한 소유역 구분)

  • 한원식;우남칠;이기철;이광식
    • Journal of Soil and Groundwater Environment
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    • v.7 no.3
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    • pp.19-32
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    • 2002
  • This study is objected to identify the relations between surface- and shallow ground-water and the seasonal variation of their qualities in watersheds near Muju area. The water type shows mainly Ca-$HCO_3$type. Heavy-metal contamination of surface water is locally detected, due to the mixing with mine drainage. In October nitrate concentration is especially high in densely populated area. Cluster Analysis and Principal Component Analysis are implemented to interpret the complexity of the chemical variation of surface- and ground-water with large amount of chemical data. Based on the cluster analysis, surface-water was divided into five groups and ground-water into three groups. Principal Component Analysis efficiently supports the result of cluster analysis, allowing the identification of three main factors controlling the water quality. There are (1) hydrogeochemical factor, (2) anthropogenic factor and (3) heavy metal contaminated by mine drainage.

Factor Analysis of Uncertainty Experienced by Patients having Rheumatoid Arthritis (류마티스 관절염 환자가 지각하는 불확실성 개념의 요인분석)

  • Yoo, Kyoung-Hee;Lee, Eun-Ok
    • Journal of muscle and joint health
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    • v.4 no.2
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    • pp.238-248
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    • 1997
  • This study was conducted to identify the characteristics of uncertainty in patients having rheumatoid arthritis. Subjects of the study constituted 528 patients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. A self report questionnaire was used to measure the uncertainty. Reliability coefficients of this instrument was found Cronbach's ${\alpha}=.84$. In data analysis, SPSS PC 6.0 computer program was utilized for descriptive statistics and factor analysis. Three factors were appointed on the basis of literature review for the principal component factor analysis method and Varimax Orthogonal Rotation. The results of factor analysis were as follows ; 1) Three factors for uncertainty were identified through the principal component analysis and varimax rotation, and these contributed 37.4% of the valiance in the total score. Twenty six items among the whole items in the scale loaded above .39 on one of 3 factors. 2) The naming of each factor was as follows : Factor 1 was 'ambiguity' and has 12 items, factor 2 was 'lack of information' and has 8 items, factor 3 was 'unpredictability' and has 7 items. 3) Cronbach's alpha for internal consistency was .84 for the total items and .81, .80, .50 for each of three subscales in that order.

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Performance Improvement of Polynomial Adaline by Using Dimension Reduction of Independent Variables (독립변수의 차원감소에 의한 Polynomial Adaline의 성능개선)

  • Cho, Yong-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.5 no.1
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    • pp.33-38
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    • 2002
  • This paper proposes an efficient method for improving the performance of polynomial adaline using the dimension reduction of independent variables. The adaptive principal component analysis is applied for reducing the dimension by extracting efficiently the features of the given independent variables. It can be solved the problems due to high dimensional input data in the polynomial adaline that the principal component analysis converts input data into set of statistically independent features. The proposed polynomial adaline has been applied to classify the patterns. The simulation results shows that the proposed polynomial adaline has better performances of the classification for test patterns, in comparison with those using the conventional polynomial adaline. Also, it is affected less by the scope of the smoothing factor.

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International Inflation Synchronization and Implications

  • CHON, SORA
    • KDI Journal of Economic Policy
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    • v.42 no.2
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    • pp.57-84
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    • 2020
  • This study analyzes global inflation synchronization and derives policy implications for the Korean economy. Unlike previous studies that assume a single global inflation factor, this study investigates if inflation in Korea can be explained further by other global inflation factors. Our principal component analysis provides three principal components for global inflation that are linked to the Korea inflation rate - the first component is closely related to OECD inflation, and the second and third components reflect China's inflation. This study empirically demonstrates via in-sample fitting and out-of-sample forecasting that the three principal components of global inflation play a significant role in explaining and predicting Korean inflation in the short-term, while their role is limited in the mid-term. Domestic macroeconomic variables are found to be more important for the mid-term movements of the Korean inflation rate. The empirical results here suggest that the Bank of Korea should focus more on domestic economic conditions than on global inflation when implementing monetary policy because global factors are likely to be already reflected in domestic macro-variables in the mid-term.

An interpretation of anthropometric data by principal component analysis

  • B.C. Yoo;Park, I.S.;Lee, S.D.;Kim, Y.S.
    • Proceedings of the ESK Conference
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    • 1996.10a
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    • pp.225-231
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    • 1996
  • The purpose of this study is providing basic information to make torso and original design of clothing of the old. Grasping the body of the old was advanced and made specific types. The objects of this study are 320 people whose age is 60 .approx. 85 and we extracted forming factors of a body by factor analysis about 57 items and we made types of a body by cluster analysis. Principal component analysis which is one of the basic methods in factor analysis was applied to the interpretation of anthropometric data. As a result of data are able to be decided into appropriate group

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Classification and Characteristic Comparison of Groundwater Level Variation in Jeju Island Using Principal Component Analysis and Cluster Analysis (주성분분석 및 군집분석을 이용한 제주도 지하수위 변동 유형 분류 및 특성 비교)

  • Lim, Woo-Ri;Hamm, Se-Yeong;Lee, Chung-Mo
    • Journal of Soil and Groundwater Environment
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    • v.27 no.6
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    • pp.22-36
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    • 2022
  • Water resources in Jeju Island are dependent virtually entirely on groundwater. For groundwater resources, drought damage can cause environmental and economic losses because it progresses slowly and occurs for a long time in a large area. Therefore, this study quantitatively evaluated groundwater level fluctuations using principal component and cluster analyses for 42 monitoring wells in Jeju Island, and further identified the types of groundwater fluctuations caused by drought. As a result of principal component analysis for the monthly average groundwater level during 2005-2019 and the daily average groundwater level during the dry season, it was found that the first three principal components account for most of the variance 74.5-93.5% of the total data. In the cluster analysis using these three principal components, most of wells belong to Cluster 1, and seasonal characteristics have a significant impact on groundwater fluctuations. However, wells belonging to Cluster 2 with high factor loadings of components 2 and 3 affected by groundwater pumping, tide levels, and nearby surface water are mainly distributed on the west coast. Based on these results, it is expected that groundwater in the western area will be more vulnerable to saltwater intrusion and groundwater depletion caused by drought.

Factor Analysis for Improving Adults' Internet Addiction Diagnosis (성인 인터넷 중독진단 개선을 위한 요인분석)

  • Kim, Jong-Wan;Kim, Hee-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.3
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    • pp.317-322
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    • 2011
  • Korean adults' internet addiction diagnosis measure, K-scale developed by Korea National Information Society Agency (NIA), has composed of 4 categories including 20 items. This scale can diagnose user's internet addiction with individual's questionnaire items. Most of previous research works were tried to know reasons of internet addiction and to judge whether adolescents are addicted or not with their samples. In this research, it is the goal to find the key component to judge individual's internet addiction by using a decision tree in the data mining field and a principal component analysis in statistics. From the experimental results, we would discover that tolerance and preoccupation factor is the most important one to affect adult's internet addiction.

Application of Multivariate Statistical Techniques to Analyze the Pollution Characteristics of Major Tributaries of the Nakdong River (낙동강 주요 지류의 오염특성 분석을 위한 다변량 통계기법의 적용)

  • Park, Jaebeom;Kal, Byungseok;Kim, Seongmin
    • Journal of Wetlands Research
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    • v.21 no.3
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    • pp.215-223
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    • 2019
  • In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.

Certifying the Quality of Electronic Commerce Services (전자상거래 서비스 품질 인증에 관한 연구)

  • Choi, Doug-W.
    • Journal of Korean Society for Quality Management
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    • v.33 no.2
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    • pp.1-12
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    • 2005
  • An extensive literature review has been made in this paper to build the evaluation hierarchy structure for the certification of electronic commerce services. In building the evaluation hierarchy structure, major candidate evaluation factors are selected by bench marking the various certification practices, including the Malcolm Baldrige award, ISO9000, and BSC(balanced scorecard) techniques. This paper deployed principal component analysis and factor analysis techniques to develop a statistically solid and systematic evaluation model. The final evaluation model, as presented in this paper as a model for the certification of electronic commerce services, produces a numeric score on the 100% scale, which can be served as a metric for the certification decision. The AHP technique was used in converting the various qualitative and quantitative evaluation values into a single measure for the certification decision.