• Communications for Statistical Applications and Methods
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• 제25권2호
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• pp.217-234
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• 2018

Copulas are a tool for constructing multivariate distributions and formalizing the dependence structure between random variables. From copula literature review, there are a few asymmetric copulas available so far while data collected from the real world often exhibit asymmetric nature. This necessitates developing asymmetric copulas. In this study, we discuss a method to construct a new class of bivariate asymmetric copulas based on products of symmetric (sometimes asymmetric) copulas with powered arguments in order to determine if the proposed construction can offer an added value for modeling asymmetric bivariate data. With these newly constructed copulas, we investigate dependence properties and measure of association between random variables. In addition, the test of symmetry of data and the estimation of hyper-parameters by the maximum likelihood method are discussed. With two real example such as car rental data and economic indicators data, we perform the goodness-of-fit test of our proposed asymmetric copulas. For these data, some of the proposed models turned out to be successful whereas the existing copulas were mostly unsuccessful. The method of presented here can be useful in fields such as finance, climate and social science.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.706-712
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• 2006

Recursive Partial Least Squares(RPLS) method has been used for processing the on-line available multivariate chemical process data and modeling adaptive prediction model for process changes. However, RPLS method is unstable in PLS model updating because RPLS method updates PLS model by merging past PLS model and new data. In this study, Adaptive Predictive Partial Least Squres(APPLS) method is suggested for more sensitive adaptation to process changes. By expanding APPLS method, block-wise Adaptive Predictive Partial Least Squares(block-wise APPLS) method is suggested for a lager scale data of chemical processes. APPLS method has been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PTT), and block-wise APPLS method has been applied to predict the cetane number using NIR Diesel Spectra data. APPLS and block-wise APPLS methods show better prediction and updating performance than RPLS method.

• 한국도로학회논문집
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• 제14권5호
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• pp.189-199
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• 2012

PURPOSES: The purpose of this study is to propose a new methodology for developing statistical collision models and to show the validation results of the methodology. METHODS: A new modeling method of introducing variables into the model one by one in a multiplicative form is suggested. A method for choosing explanatory variables to be introduced into the model is explained. A method for determining functional forms for each explanatory variable is introduced as well as a parameter estimating procedure. A model selection method is also dealt with. Finally, the validation results is provided to demonstrate the efficacy of the final models developed using the method suggested in this study. RESULTS: According to the results of the validation for the total and injury collisions, the predictive powers of the models developed using the method suggested in this study were better than those of generalized linear models for the same data. CONCLUSIONS: Using the methodology suggested in this study, we could develop better statistical collision models having better predictive powers. This was because the methodology enabled us to find the relationships between dependant variable and each explanatory variable individually and to find the functional forms for the relationships which can be more likely non-linear.

• 디지털산업정보학회논문지
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• 제8권4호
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• pp.205-215
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• 2012

Due to a rapid change of business environment, many firms are eager to find the competitiveness by information technology adoption and diffusion. In this exploratory study, we examined the applicability of a previously proposed model to evaluate IT competitiveness based on the innovativeness and verified it's propriety with empirical data. As suggested by previous studies, the proposed model considers a variety of corporate and market characteristics concerned with IT adoption, and it consists of several internal and external impacting factors, which have influence on technology diffusion and its performance. For the empirical analysis, the survey data of domestic ERP adoption cases were adopted from 128 small and medium-sized enterprises(: SMEs) in IT and electrical engineering industry, and analyzed by partial least squares(: PLS) - a popular structural modeling and multivariate projection technique to latent variables. The results indicated positive supports for the research model of external and internal IT adoption factors' influences on innovativeness' performances. However, there are a couple of limitations not to show the reliability of selected measurement items and the generality of model proposed in this exploratory study.

• 한국정밀공학회지
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• 제34권2호
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• pp.125-131
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• 2017

2-Axis Pan and Tilt Motion Platform, a complex multivariate non-linear system, may incur any disturbance, thus requiring system controller with robustness against various disturbances. In this study, we designed an adaptive backstepping compensated controller by estimating the disturbance and error using the Radial Basis Function Neural Network (RBF NN). In this process, Uniformly Ultimately Bounded (UUB) was demonstrated via Lyapunov and stability was confirmed. By generating progressive disturbance to the irregular frequency and amplitude changes, it was verified for various environmental disturbances. In addition, by setting the RBF NN input vector to the minimum, the estimated disturbance compensation process was analyzed. Only two input vectors facilitated compensatory function of RBF NN via estimating the modeling and control error values as well as irregular disturbance; the application of the process resulted in improved backstepping controller performance that was confirmed through simulation.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.267-273
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• 2020

With the strong growth of social networking sites such as Facebook in recent years, the potential of exploiting customers on Facebook is increasing. Presently, trading activities on Facebook is rapidly developing. Therefore, businesses have become increasingly competitive when selling products on Facebook, so as to retain customers as well as to satisfy customer, which is of paramount importance. This study was conducted to assess the factors affecting the satisfaction of individual customers in Vietnam when buying goods on Facebook. This study uses multivariate analysis techniques (Confirmatory Factor Analysis, Structural Equation Modeling) to determine the factors affecting customer satisfaction when buying goods on Facebook. Research results from 268 individual customers in Vietnam indicated trust and convenience are the two important factors related to customer satisfaction when buying goods on Facebook. Customer satisfaction is the result of consumer experience throughout the different stages of purchase. The more the shopping experience, the more the customers are satisfied when buying products. The price and products do not affect customer satisfaction (prices are easy to compare and products are easily understood on the Internet; hence, these two factors are not considered as determinants of customer satisfaction). Furthermore, this study provides recommendations to improve customer satisfaction.

• Journal of Gastric Cancer
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• 제16권2호
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• pp.78-84
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• 2016

Purpose: The aim of this study was to determine whether surgical resection of the primary tumor contributes to survival in patients with metastatic gastric cancer. Materials and Methods: A total of 288 patients with metastatic gastric cancer from the Akdeniz University, Antalya Training and Research Hospital, and the Meram University of Konya database were retrospectively analyzed. The effect of primary tumor resection on survival of patients with metastatic gastric cancer was investigated using the log-rank test. Kaplan-Meier survival estimates were calculated. Multivariate analysis was performed using Cox proportional hazards regression modeling. Results: The median overall survival was 12.0 months (95% confidence intewrval [CI], 10.4~13.6 months) and 7.8 months (95% CI, 5.5~10.0 months) for patients with and without primary tumor resection, respectively (P<0.001). The median progression-free survival was 8.3 months (95% CI, 7.1~9.5 months) and 6.2 months (95% CI, 5.8~6.7 months) for patients with and without primary tumor resection, respectively (P=0.002). Conclusions: Non-curative gastrectomy in patients with metastatic gastric cancer might increase their survival rate regardless of the occurrence of life-threatening tumor-related complications.

• Industrial Engineering and Management Systems
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• 제15권1호
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• pp.110-121
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• 2016

With the growing interest in skincare and maintenance, there are increasing numbers of studies on the classification of skin type and the factors influencing each type. This study presents a novel methodology by using data mining, for the determination of the relationships between skin type, lifestyle, and patterns of cosmetic utilization. Eight skin-specific factors, which are moisture, sebum in U-zone (both cheeks), sebum in T-zone (forehead, nose, and chin), pore, melanin, wrinkle, acne, hemoglobin, were measured in 1,246 subjects living in South Korea, in conjunction with a questionnaire survey analyzing their lifestyles and pattern of cosmetic utilization. Using various multivariate statistical methods and data mining techniques, we classified the skin types based on the skin-specific values, determined the relationship between skin type and lifestyle, and accordingly sorted the subjects into clusters. Logistic regression analysis revealed gender-related differences in the skin; therefore, separate analyses were performed for males and females. Using the Gaussian Mixture Modeling (GMM) technique, we classified the subjects based on skin type (two male and four female). Using the ANOVA and decision tree techniques, we attempted to characterize the relationship between each skin type and the lifestyles of the subjects. Menstruation, eating habits, stress, and smoking were identified as the major factors affecting the skin.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.285-295
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• 2021

This study estimates the influence of organizational-level factors on work motivation and job performance of middle managers of small and medium enterprises (SMEs) in Vietnam. A 5-point-Likert-scale structural questionnaire consisting of 36 observation variables was used to survey middle managers of Vietnamese SMEs. 425 out of 500 responses collected were valid for multivariate data analysis. The results of confirmatory factor analysis and structural equation modeling reveal three main findings. First, philosophy and policy, compensation and benefits, goal system, and leadership have positively significant impacts on the work motivation of middle managers under investigation. Second, there is a significantly positive influence of work motivation on job performance. However, there is no indication that growth opportunities, work environment, evaluation system have significant impacts on the work motivation of respondents. Based on the findings, the study suggests four recommendations for Vietnamese SMEs to improve motivation and job performance of middle managers, which are (1) ensuring the clarity and soundness of the organizational policies and philosophies, especially human resources policy that boosts employees' work motivation; (2) building a comprehensive compensation and benefit system to attract and retain talented employees; (3) developing a clear and adequate goal system; (4) enhancing top-level managers' leadership abilities.

• Computers and Concrete
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• 제27권4호
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• pp.305-317
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• 2021

The bond between the concrete and bar is a main factor affecting the performance of the reinforced concrete (RC) members, and since the steel corrosion reduces the bond strength, studying the bond behavior of concrete and GFRP bars is quite necessary. In this research, a database including 112 concrete beam test specimens reinforced with spliced GFRP bars in the splitting failure mode has been collected and used to estimate the concrete-GFRP bar bond strength. This paper aims to accurately estimate the bond strength of spliced GFRP bars in concrete beams by applying three soft computing models including multivariate adaptive regression spline (MARS), Kriging, and M5 model tree. Since the selection of regularization parameters greatly affects the fitting of MARS, Kriging, and M5 models, the regularization parameters have been so optimized as to maximize the training data convergence coefficient. Three hybrid model coupling soft computing methods and genetic algorithm is proposed to automatically perform the trial and error process for finding appropriate modeling regularization parameters. Results have shown that proposed models have significantly increased the prediction accuracy compared to previous models. The proposed MARS, Kriging, and M5 models have improved the convergence coefficient by about 65, 63 and 49%, respectively, compared to the best previous model.