• 제목/요약/키워드: Multiple Discriminant Analysis

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Local Influence Assessment of the Misclassification Probability in Multiple Discriminant Analysis

  • Jung, Kang-Mo
    • Journal of the Korean Statistical Society
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    • 제27권4호
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    • pp.471-483
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    • 1998
  • The influence of observations on the misclassification probability in multiple discriminant analysis under the equal covariance assumption is investigated by the local influence method. Under an appropriate perturbation we can get information about influential observations and outliers by studying the curvatures and the associated direction vectors of the perturbation-formed surface of the misclassification probability. We show that the influence function method gives essentially the same information as the direction vector of the maximum slope. An illustrative example is given for the effectiveness of the local influence method.

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Some Diagnostic Results in Discriminant Analysis

  • Bae, Whasoo;Hwang, Soonyoung
    • Journal of the Korean Statistical Society
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    • 제30권1호
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    • pp.139-151
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    • 2001
  • Although lots of works are done in influence diagnostics, results in the multivariate analysis are quite rare. One of recent works done by Fung(1995) is about the single case influence diagnostics in the linear discriminant analysis. In this paper we extend Fung's results to the multiple cases diagnostics which are necessary in the linear discriminant analysis for two reasons among others; First, the masking effect cannot be detected by single case diagnostics and secondly two populations are concerned in the discriminant analysis, i.e., influential cases can occur in one or both populations.

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판별분석을 통한 패밀리레스토랑의 고객 분류와 마케팅전략에 관한 연구 (A Multiple Discriminant Approach to Identifying Frequent Users of Eating out at Family Restaurant)

  • 강종헌
    • 한국식품조리과학회지
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    • 제18권1호
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    • pp.109-118
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    • 2002
  • The purpose of this study was to identify the behavioral, attitudinal, and demographic correlates of light, medium, and heavy users of eating out at family restaurants. Among 358 reponses from the subjects, 224 responses were utilized for the analysis, and 134 responses were reserved for validating the discriminant function. Descriptive statistics, reliability analysis, stepwise discriminant analysis, canonical discriminant analysis, and anova analysis were used for this study. The findings from this study were as follows: First, He behavioral characteristics were found to discriminate among the three usage groups. Second, it was found that heavy users expressed greater difference between perception and expectation on the quantity of food that are appropriately served and the consistent quality of food at every visit. Third, the usage rate of eating out was not dependent on the sex, but dependent on the companion, average expenditure, and the time of eating out in chi-square test. Finally, the results of the study provide some insight into the pattern of marketing strategies that can be successfully used by the managers of family restaurants.

아동의 또래괴롭힘 참여유형의 판별변인 분석 (Discriminant Analysis of Bullying Participant Roles among Children)

  • 김연화;한세영
    • 아동학회지
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    • 제32권3호
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    • pp.19-41
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    • 2011
  • This paper was an examination of gender-specific behaviors in children and the types of bullying behavior among 1,181 fifth and sixth grade elementary schools student identified were then classified. Differences were identified in individual variables, family variables, and school variables. The data thus collected were subjected to descriptive and comparative statistical analysis using the SPSS software program. Our results showed that multiple discriminant analysis yielded a function of individual, family and school variables that proved effective in classifying bully, reinforcer, assistant, victim, outsider and defender types in boys. In girls, multiple discriminant analysis yielded a function of individual variables that was effective in classifying bully, reinforcer, assistant, victim, outsider and defender types.

Local Influence in Quadratic Discriminant Analysis

  • Jung, Kang-Mo
    • Communications for Statistical Applications and Methods
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    • 제6권1호
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    • pp.43-52
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    • 1999
  • The local influence method is adapted to quadratic discriminant analysis for the identification of influential observations affecting the estimation of probability density function probabilities and log odds. The method allows a simultaneous perturbation on all observations so that it can identify multiple influential observations. The proposed method is applied to a real data set and satisfactory result is obtained.

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A Bayesian Diagnostic Measure and Stopping Rule for Detecting Influential Observations in Discriminant Analysis

  • Kim, Myung-Cheol;Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • 제29권3호
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    • pp.337-350
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    • 2000
  • This paper suggests a new diagnostic measure and a stopping rule for detecting influential observations in multiple discriminant analysis (MDA). It is developed from a Bayesian point of view using a default Bayes factor obtained from the fractional Bayes factor methodology. The Bayes factor is taken as a discriminatory information in MDA. It is shown that the effect of an observation over the discriminatory information is fully explained by the diagnostic measure. Based on the measure, we suggest a stopping rule for detecting influential observations in a given training sample. As a tool for interpreting the measure a graphical method is sued. Performance of the method is used. Performance of the method is examined through two illustrative examples.

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Monolith and Partition Schemes with LDA and Neural Networks as Detector Units for Induction Motor Broken Rotor Bar Fault Detection

  • Ayhan Bulent;Chow Mo-Yuen;Song Myung-Hyun
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • 제5B권2호
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    • pp.103-110
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    • 2005
  • Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different load conditions. Multiple Discriminant Analysis (MDA) and Artificial Neural Networks (ANN) provide appropriate environments to develop such fault detection schemes because of their multi-input processing capabilities. This paper describes two fault detection schemes for broken rotor bar fault detection with multiple signature processing, and demonstrates that multiple signature processing is more efficient than single signature processing.

New Methodology to Develop Multi-parametric Measure of Heart Rate Variability Diagnosing Cardiovascular Disease

  • Jin, Seung-Hyun;Kim, Wuon-Shik;Park, Yong-Ki
    • International Journal of Vascular Biomedical Engineering
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    • 제3권2호
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    • pp.17-24
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    • 2005
  • The main purpose of our study is to propose a new methodology to develop the multi-parametric measure including linear and nonlinear measures of heart rate variability diagnosing cardiovascular disease. We recorded electrocardiogram for three recumbent postures; the supine, left lateral, and right lateral postures. Twenty control subjects (age: $56.70{\pm}9.23$ years), 51 patients with angina pectoris (age: $59.98{\pm}8.41$ years) and 13 patients with acute coronary syndrome (age: $59.08{\pm}9.86$ years) participated in this study. To develop the multi-parametric measure of HRV, we used the multiple discriminant analysis method among statistical techniques. As a result, the multiple discriminant analysis gave 75.0% of goodness of fit. When the linear and nonlinear measures of HRV are individually used as a clinical tool to diagnose cardiac autonomic function, there is quite a possibility that the wrong results will be obtained due to each measure has different characteristics. Although our study is a preliminary one, we suggest that the multi-parametric measure, which takes into consideration the whole possible linear and nonlinear measures of HRV, may be helpful to diagnose the cardiovascular disease as a diagnostic supplementary tool.

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외식프랜차이즈기업 부실예측모형 예측력 평가 (Evaluating Distress Prediction Models for Food Service Franchise Industry)

  • 김시중
    • 유통과학연구
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    • 제17권11호
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    • pp.73-79
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    • 2019
  • Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

특용작물의 산지판별을 위한 전자코 응용 (Application of Electronic Nose in Discrimination of the Habitat for Special Agricultural Products)

  • 노봉수;고재원;김상용;김수정
    • 한국식품과학회지
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    • 제30권5호
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    • pp.1051-1057
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    • 1998
  • 영지, 참깨, 칡과 같은 특용작물의 수입산 또는 국내산인지의 여부를 확인하기 위하여 전자코를 사용하였다. 특용작물이 배출하는 가스성분을 아무런 전처리 과정 없이 12개의 conducting polymer sensor로 감지하고 여기서 얻어진 자료를 판별분석을 통하여 특용작물의 원산지가 수입산 또는 국내산인지를 판별할 수 있었다. 원산지를 모르는 시료(영지, 참깨)를 분석한 결과 이들 농산물이 수입산인지 국내산인지를 뚜렷하게 구별할 수 있었다.

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