• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.223-236
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• 2013

Various statistical classification methods to predict election to the Major League Baseball hall of fame of are implemented and their accuracies are compared. Seventeen independent variables are selected from the data of candidates eligible for the hall of fame and well-known classification methods such as discriminant analysis and logistic regression as well as the recently proposed Mahalanobis-Taguchi system(MTS). The MTS showed a better performance than the others in classification accuracy because it is especially efficient in cases where multivariate data does not constitute directionally geographical groups according to attributes.

• Fashion & Textile Research Journal
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• v.26 no.1
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• pp.35-43
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• 2024

This study aimed to objectively classify the lateral torso posture types and functions of older women. We used 3D body scan data of 119 women aged 70-85 years from the 6th SizeKorea project. First, we defined three torso axes to represent the lateral torso posture types: posterior waist-back, back-cervical, and whole torso axes. Next, we asked experts to select one of four lateral torso posture types-stooped, straight, leaning back, and swayback postures-by looking at the lateral photographic data of 119 older women. To identify the axis that best represented each lateral torso posture type, a discriminant analysis was conducted using the angle of each of the three torso axes as an independent variable and an expert's visual classification as a dependent variable. Based on the analysis, the whole torso and backcervical axis angles were selected as variables for judging lateral torso posture types. Subsequently, we developed a classification function to determine which of the four lateral torso posture types of a particular participant was applicable for a new individual. The method developed in this study is significant in that it enables the objective classification of the lateral torso postures types of older women.

• Korea Journal of Hospital Management
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• v.6 no.3
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• pp.130-147
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• 2001

This study is about major symptoms of elderly and medical services for elderly in long-tenn care facilities. The subject of this study was 298 patients over 00 years old staying in two geriatric hospitals and two nursing homes. The symptoms and medical services were level of patient classification from RUG(Resource Utilization Group)-III which is applied for both Medicare and Medicaid for skilled nursing facilities reimbursement system in US and designed for measuring patient characteristics and medical staff time. This classification is explained by each patient resource(staff time) utilization level which is called CMI(Case-Mix Index). In this study, the symptoms and services were compared by facility type and they were categorized by level and compared by CMI. Major findings are as follows; 1. There were more elderly who have cognitive function problems in nursing homes than patients in geriatric hospitals. There were more patients with behavioral problems in geriatric hospitals than residents in nursing homes. These results were both statistically significant. 2. The patients in geriatric hospitals received significantly more nursing rehabilitation services, rehabilitation services and extensive services than residents in nursing homes. Other hands, special care services were provided significantly more to residents in nursing homes than elderly in geriatric hospitals. 3. ADL and depression variables had higher CMI when the symptoms were heavier condition. The CMI were not matched with levels of cognitive function problems and behavioral problems. 4. The CMI matched well significantly with levels of nursing rehabilitation services, special care services, and clinically complex services provided for the patient in geriatric hospitals and only nursing rehabilitation services in nursing homes. The CMI for rehabilitation services level and extensive services had regular trends. From the result of this study, the resource utilization level and services provided for elderly in each long-term care facilities were figured out. For the further study, it needs to have more concern about RUG-ill which classification variables were just analyzed.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.73-86
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• 2024

A radial chart of Excel is very useful graphical method in delivering information for numerical data. However, it is not easy to discriminate or classify many individuals. In this case, after shaping each individual of a radial chart, we need to apply shape analysis. For a radial chart, since landmarks for shaping are formed as many as the number of variables representing the characteristics of the object, we consider a shape that connects them to a line. If the shape becomes complicated due to the large number of variables, it is difficult to easily grasp even if visualized using a radial chart. Principal component analysis (PCA) is performed on variables to create a visually effective shape. The classification table and classification rate are checked by applying the techniques of traditional discriminant analysis, support vector machine (SVM), and artificial neural network (ANN), before and after principal component analysis. In addition, the difference in discrimination between the two coordinates of generalized procrustes analysis (GPA) coordinates and Bookstein coordinates is compared. Bookstein coordinates are obtained by converting the position, rotation, and scale of the shape around the base landmarks, and show higher rate than GPA coordinates for the classification rate.

• Journal of Korean Society of Forest Science
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• v.81 no.3
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• pp.214-223
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• 1992

To investigate the structure of the plant community of Mt. Jookyup area in Kwangnung forest, thirty-seven plots were set up by the clumped sampling method. The classification by TWINSPAN and two kinds of multivariate ordination(RA, DCA) were applied to the study area in order to classify them into several groups based on woody plants and environmental variables. The classification have been successfully overlayed on an ordination of the same data using DCA. The plots can be classified into five groups by TWINSPAN and DCA. The successional trends of tree species by both techniques seem to be expected two ways in the canopy layer. The first is from Pinus densiflora to Carpinus laxiflora and the second is from Pinus densiflora through Quercus mongolica to Carpinus laxiflora. In the understory layer, it was expected that Rhododendron mucronulatum ${\rightarrow}$Lindera obtusiloba, Symplocos chinensis for. pilosa, Viburunum erasum, Styrax obassia${\rightarrow}$Euonymus sachalinensis, Sorbus alnifolia. As the result of the analysis for the relationship between the stand scores of DCA and environmental variables, they had a tendency to increase significantly from the P. densiflora community to Quercus spp. community that was soil pH, total nitrogen, available phosphate and exchangeable potassium, sodium, calcium and magnesium.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.3
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• pp.237-245
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• 2004

In designing a tunnel, RMR has been widely used to classify rock mass and to decide the support pattern according to the class of rock mass. However, this RMS system can't help relying on the empirical judgment of engineers who use variables which can be obtained only through consideration of the site conditions. In actuality, it is impossible to consider all the rating factors of RMS when using RMR system at the stage of designing. Therefore, in order to confirm possibility of RMR by use of only the quantitative factors for designing, this paper has done discriminant analysis. Rock strength or RQD has high coefficient of correlation with RMR value, and in consideration of the existing standards for rock mass classification, rock intensity and RQD are important factors for classification of rock mass. Through rock mass classification by the existing RMR system and rock mass classification by the discriminant analysis which has considered two variables only, the discriminant analysis using the rock intensity as an independent variable has shown 74.8% accuracy while the discriminant analysis using RQD as an independent variable has shown 74.3% accuracy. In case of the discriminant analysis which has considered both rock intensity and RQD, it has shown 82.5% accuracy. The existing cases have shown 40.3% accuracy at the stage of designing in which all the RMR factors are considered. It means that at the stage of designing, RMR system can work only with the rock intensity and RQD.

• Journal of Veterinary Clinics
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• v.33 no.2
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• pp.107-112
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• 2016

The objective of this study was to determine potential contributing factors associated with biosecurity level of farrow-to-finish pig farms and to develop a classification tree model to explore how these factors related to each other based on prediction model. To this end, the author analyzed data (n = 193) extracted from a cross-sectional study of 344 farrow-to-finish farms which was conducted between March and September 2014 aimed to explore swine disease status at farm level. Standardized questionnaires with information about basic demographical data and management practices were collected in each farm by on-site visit of trained veterinarians. For the classification of the data sets regarding biosecurity level as a dependent variable and predictor variables, Chi-squared Automatic Interaction Detection (CHAID) algorithm was applied for modeling classification tree. The statistics of misclassification risk was used to evaluate the fitness of the model in terms of prediction results. Categorical multivariate input data (40 variables) was used to construct a classification tree, and the target variable was biosecurity level dichotomized into low versus high. In general, the level of biosecurity was lower in the majority of farms studied, mainly due to the limited implementation of on-farm basic biosecurity measures aimed at controlling the potential introduction and transmission of swine diseases. The CHAID model illustrated the relative importance of significant predictors in explaining the level of biosecurity; maintenance of medical records of treatment and vaccination, use of dedicated clothing to enter the farm, installing fence surrounding the farm perimeter, and periodic monitoring of the herd using written biosecurity plan in place. The misclassification risk estimate of the prediction model was 0.145 with the standard error of 0.025, indicating that 85.5% of the cases could be classified correctly by using the decision rule based on the current tree. Although CHAID approach could provide detailed information and insight about interactions among factors associated with biosecurity level, further evaluation of potential bias intervened in the course of data collection should be included in future studies. In addition, there is still need to validate findings through the external dataset with larger sample size to improve the external validity of the current model.

• Journal of Korean Society of Forest Science
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• v.79 no.2
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• pp.173-186
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• 1990

To investigate the structure of the plant community of Soribong area in Kwangnung forest, forty-six plots were set up by the clumped sampling method. The classification by TWINSPAN and four kinds of multivariate ordination(PO, PCA, RA, DCA) were applied to the study area in order to classify them into several groups based on woody plants and environmental variables. The classification had been successfully overlayed on an ordination of the same data using DCA. The plots can be classified into four groups by TWINSPAN and DCA. The successional trends of tree species by both techniques seem to be from Pinus densiflora through Quercus mongolica, Q. serrata, Q. aliena, Carpinus laxiflora, Sorbus alnifolia to C. cordata, Fraxinus rhynchophylla, Cornus controversa in the canopy layer, and from Rhododendron mucronulatum, Rhus triohocarpa, Lespeoleza cyrtobotrya, Weigela subsessilis through Corylus sieboldiana, Lindera obtusiloba to Slaphylea bumalda, Callicarpa japonica, Lonicera maackii in the understory layer. As a result of the analysis for the relationship between the stand scores of DCA and environmental variables, they had a tendancy to increase significantly from the P. densiflora community to C. cordata community that was soil pH and the amount of humus, total nitrogen and exchangeable cations.

• Journal of Families and Better Life
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• v.22 no.2
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• pp.85-95
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• 2004

The purpose of this study was to classify the household financial strategies and find out variables affecting the type of the household financial strategies. The data of 3994 households from Korean Labor and Income Panel Study(1999-2000) were used. The major findings were as follows: (1) the household financial strategies were Residual Saver Type(44.6%), Unformal Institute Saver Type(13.3%), Financial asset Saver Type(16.7%), Real estate Saver Type(13.4%) and Diversities(12.0%). (2) The household financial strategy types were changed rapidly during short term. (3) In 3994 households, the variables which influence on the change of the household financial strategies were education, job, numbers of children, place of residence, home ownership. Similarly, in each type, the change of household financial strategies was significantly different according to the household characteristics variables.

• Proceedings of the Safety Management and Science Conference
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• 2006.04a
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• pp.471-484
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• 2006

The focus of analysis is effect on Non-electrical Machinery and Equipment of Macroeconomic variables through long-term and short-term periods. Also, this paper is related with implication on steady growth possibility of Non-electrical Machinery and Equipment. The period of variables is from 1985 to April in 2005. In case of not-available data is treated as missing figures. As spatial scope, these data are Non-electrical Machinery and Equipment on the basis of KSIC. In case of items, it composes MTI 1&3 digit of Korea International Trade Association (KITA), on the basis of HSK & classification of Korea Machinery industries. According to Granger causality test, yield of Cooperate Bond and export amount of Machinery have a meaning at statistical Confidence level of 10%. In case of index of the unit cost of export and export amount of Machinery, they have an interactive Granger cause. In yen dollar exchange rate and export amount of Machinery, former variable gives an unilateral Granger cause to latter that.