• The Research Journal of the Costume Culture
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• v.8 no.6
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• pp.930-939
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• 2000

This study was done to provide the fundamental data for scientific and rational children's clothing sizing system by investigating their somatometric characteristics and classifying somatotypes. The subjects were 269 elementary schoolgirls aged from 7 to 8 years old living in Pusan and Kyungsangnam-do. Data from each girl comprises 28 anthropometic measurments and 4 photographic measurments, related to the lower half of body. To analyze somatotypes of the lower half of body, factor analysis, cluster analysis, discriminant analysis were performed for statistical analysis of the data. As to the analysis to draw somatometric factors by this age group, five factors which explain 76.85% of the whole variances were extracted. The first and second factors which explain more than 60% of the whole variances represent 'horizontal size'and 'vertical size', which characterize most aspects of the body shape of the subjects. On the basis of the cluster analysis, three different lower half of body types were categorized. Type Ⅰ has biggest horizontal size, average vertical size and most protruded belly. Type Ⅱ has average degree of horizontal size, quite big vertical size and most protruded hips. Type Ⅲ has smallest horizontal and vertical size. According to the analysis to discriminate somatotypes of the lower half of body of this age group, weight and waist circumference of discriminant function 1 and abdominal circumference of discriminant function 2 have coefficient values.

• Korean Journal of Child Studies
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• v.32 no.3
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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.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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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.

• Journal of Korean Academy of Nursing
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• v.16 no.2
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• pp.63-69
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• 1986

The main purpose of this study was to find out variables relevant to self-care activities of physically disabled person. The subjects of this analysis were 1277 person which is between 15~64 years, the data came from the 1985 National Interview Survey on Disabled Person in Korea. For this analysis, Breakdown, Oneway and Discriminant Analysis were used. The finding of the analysis can be summarized as follows: First, the mean of self care activities was 2.57 (SD: 0.69, range: 1-3). The relevance for the self-care activities by several variables is as follows. 1. The relevance for the self-care activities by socioeconomic status is significant at age, education level, occupation of household members variables. Especially, in the case of high age, low education level, the self-care activities are shown low score. 2. The relevance by impairment characteristics is shown high significance at all input variables. When disabled person have double impairment. paralysis, late occurance age, and is due to diseases the self-care activities score is lowered. 3. The relevance by health care services variables. is not shown significant at all input variables. Second, the relevance for social activities by sev-eral variables was conducted by discriminant analysis. The relative importance of social activities discriminant function is 0.344 of eigenvalue. The-canonical correlation between the social activities discriminant function and 9 dummy variables is 0.51, total variance of dummy variables for social activities is shown 26 persent. The self-care activities variable represents the highest contribution of its associated variable to the function (canonical coefficient: -.56). The occurance age, the occupation of household members, the education level variables are shown comparatively high contribution to the function. To sum up, this analysis suggests that the self-care activities variable is the highest contributed to the social activities. In relation to self-care concept, this finding will be useful in rehabilitation nursing care.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.499-509
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• 2001

We investigate the influence of observations on a test of additional information about discrimination using the influence function and the derivative influence measures. the influence function for the test statistic is derived and this sample versions are used for influence analysis. The derivative influence measures for the test statistic under a perturbation scheme are derived. It will be seen that the influence function method and the derivative influence measures yield the same result. Furthermore, we will derive the relationships between the influence function and the derivative influence measures when the sample size is large. an illustrative example is given and we will compare the results provided by the influence function method and the derivative influence measures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.125-130
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• 2018

Linear discriminant analysis is a statistical analysis method that is generally used for dimensionality reduction of the feature vectors or for class classification. However, in the case of a data set that cannot be linearly separated, it is possible to make a linear separation by mapping a feature vector into a higher dimensional space using a nonlinear function. This method is called generalized discriminant analysis or kernel discriminant analysis. In this paper, we carried out target classification experiments with active sonar target signals available on the Internet using both liner discriminant and generalized discriminant analysis methods. Experimental results are analyzed and compared with discussions. For 104 test data, LDA method has shown correct recognition rate of 73.08%, however, GDA method achieved 95.19% that is also better than the conventional MLP or kernel-based SVM.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.22 no.1
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• pp.80-82
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• 1977

Using head length and head width of two wheat monosomic lines linear discriminant function of these two variables was calculated and also illustrated how one can effectively classify unknown individuals into a correct group belonging by means of this linear discriminant function in reverse. Brief suggestion on the utilization of this analysis in genetics and breeding program was given.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.87-100
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• 2002

Poorly-posed problems in the balanced discriminant analysis was considered. We restrict consideration to the case of observations and the number of variables are the same and small. When these problems exist, we do not use a maximum likelihood estimates(MLE) to estimate covariance matrices. Instead of MLE, an alternative estimate for the covariance matrices are proposed. This alternative method make good use of two regularization parameters, $\lambda$} and $\gamma$. A new test rule for the discriminant function is suggested and examined via limited hut informative simulation study. From the simulation study, it is shown that the suggested test rule gives better test result than other previously suggested method in terms of error rate criterion.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.467-473
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• 2011

The contractor management for the effective defense project is essential factor in the modern defense acquisition task. The occurrence of unlawful company causes hastiness for project manager and setback to the deployment of defense weapon system. In this paper, we develop a prediction model for the effective defense project by using the discriminant analysis and analyse the variables that discriminate the unlawful company in many variables. It is expected that our model can be used to improve the project management capability of defense acquisition and contribute to the establishment of efficient procurement procedure through entry of the reliable defense manufacturer.

• Journal of Korean Academy of Nursing
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• v.23 no.1
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• pp.130-141
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• 1993

This study was to find out variables influenced on the medication patterns (voluntary medication, in-voluntary medication) of antipsychotics taken by schizophrenic outpatients. Purposes of this study were to be identified that there was the significant difference between the group of voluntary medication and involuntary, and that which variables had infuence on outpsychotics medication. The sample consisted of 30 patients takeing their pills voluntary (voluntary medication group), and 15 patients involuntary(involuntary medication group) at a psychiatry hospital and a psychiatric unit of a The findings of the study are as follows : university hospital in Daegu. Data were collected from September to October, 1991 through interview using questionare about antipsychotics medication. Data were analyzed by the technique of two group discriminant function analysis using SPSS pc$^{+}$ 1) Discriminant function discriminating between voluntary medication and involuntary medication was significant at the level of 10% significance (sig.=.055, p〈.10) Hit-ratio was very high (91. 1％) 2) One of General variables, SEX, was significant of discriminating between two medication patterns at the level of 10% significance. 3) One of Family Environmental Variables, BROTH(a number of brother), were significant between two medication patterns. (p〈.10) 4) One of Therapeutic Environmental Variables, FAMHX, was significant between two medication patterns at the level of 10% significance. 5) One of Variables Related to Drug and Medication, NECESS, was significant between two medication patterns. (p〈.05) 6) Variables Related to Disease was not significant between two medication patterns.s.