• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.775-791
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• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.333-338
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• 2016

This study is to estimate proximity without direct measurement of the weight of fresh ginseng. For this work, we developed a ginseng image acquiring instrument and obtained 126 ginseng images using the instrument. Image analysis and parameter extraction process was used C language based Labwindows/CVI development tools and open source library OpenCV. Estimation formula is made by weighing the sample with image analysis of fresh ginseng. We analyzed the correlation between the pixel number and the weight of ginseng using a linear regression approach. It was obtained a strong positive correlation coefficient of 0.9162 with a linearity value.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.21-32
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• 2010

Graphical regression is a paradigm for obtaining regression information using plots without model assumptions. The general goal of this approach is to find lowdimensional sufficient summary plots without loss of important information. Model assessments using residual plots are less likely to be successful in models that are not linear. As an alternative approach, marginal model plots provide a general graphical method for assessing the model. We apply the methods of graphical regression and model assessment using marginal model plots to the logistic regression model.

• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.1017-1022
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• 2005

There are many changes in the software requirements during the whole software life cycle. These changes require modification of the software, and it is important to keep software quality and stability while we are modifying the software. Refactoring is one of the technology to keep software quality and stability during the software modification; there are many researches related to automatic refactoring. In this paper, we propose three factors for Move Method which is one of the refactoring technique. We applied binomial logistic analysis to data which were extracted from sample program by each factor. The result of this process was very close to the result of manual analysis by program experts. Furthermore, we found that these factors have major roll to determine Position of a method, and these factors can be used as a basis of finding optimal position of a method.

• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.251-266
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• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

• Journal of Service Research and Studies
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• v.3 no.1
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• pp.9-16
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• 2013

Data analysis is the universal classification techniques, which requires a lot of effort. It can be easily analyzed to understand the results. Decision tree which is developed by Breiman can be the most representative methods. There are two core contents in decision tree. One of the core content is to divide dimensional space of the independent variables repeatedly, Another is pruning using the data for evaluation. In classification problem, the response variables are categorical variables. It should be repeatedly splitting the dimension of the variable space into a multidimensional rectangular non overlapping share. Where the continuous variables, binary, or a scale of sequences, etc. varies. In this paper, we obtain the coefficients of precision, reproducibility and accuracy of the classification tree to classify and evaluate the performance of the new cases, and through experiments to evaluate.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.3
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• pp.111-118
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• 2005

It is increased electrical energy consumption with the development of intelligence society in the once buildings and thus an energy conservation through efficient use of electricity became more important. This paper shows a reasonable design demand factor in office buildings, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, peak power consumption, demand factor, etc., for 54 office buildings and 34 electrical design offices. In this dissertation it is necessary to analyse the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimum and thus it was carried the linear and nonlinear regression analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.12
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• pp.1503-1512
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• 2013

In this study, we proposed an indentation evaluation method for fracture toughness using cohesive finite element simulations. First, we examined the effect of material properties (yield strain, Poisson's ratio, and elastic modulus) on crack size during Vickers indentation and then generated a regression formula that explains the relations among fracture toughness, indentation load, and crack size. We also proposed another indentation formula for fracture toughness evaluation using the contact size a and E/H (H: hardness). Finally, we examined the relation between the crack size and the indenter shapes. Based on this, we can generate from the formula obtained using the Vickers indenter a formula for an indenter of different shapes. Using the proposed method, fracture toughness is directly estimated from indentation data.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.115-125
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• 2021

This study aims to investigate the effects of self-service technology (SST) characteristics and consumer characteristics on consumer resistance and satisfaction with SST in restaurants. An online survey was conducted for consumers in their 20s and 50s who used SST at restaurants, and 343 data were used for analysis. As a result, convenience and tech-controllability have a negative effect on consumer resistance with SST, whereas complexity, social risk and relationship orientation have a positive effect. In addition, convenience, entertainment, and tech-controllability have a positive effect on consumer satisfaction with SST, whereas social risk and relationship orientation have a negative effect. This study contributes practically and academically in that it proposes a practical strategy to reduce consumer resistance and increase satisfaction, and identifies the determinants of consumer response to SST. In future studies, an in-depth analysis of consumers' ambivalent responses to SST is required.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1057-1067
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• 2014

Many genetic variants have been identified to be associated with complex diseases such as hypertension, diabetes and cancers throughout genome-wide association studies (GWAS). However, there still exist a serious missing heritability problem since the proportion explained by genetic variants from GWAS is very weak less than 10~15%. Gene-gene interaction study may be helpful to explain the missing heritability because most of complex disease mechanisms are involved with more than one single SNP, which include multiple SNPs or gene-gene interactions. This paper focuses on gene-gene interactions with the survival phenotype by extending the multifactor dimensionality reduction (MDR) method to the accelerated failure time (AFT) model. The standardized residual from AFT model is used as a residual score for classifying multiple geno-types into high and low risk groups and algorithm of MDR is implemented. We call this method AFT-MDR and compares the power of AFT-MDR with those of Surv-MDR and Cox-MDR in simulation studies. Also a real data for leukemia Korean patients is analyzed. It was found that the power of AFT-MDR is greater than that of Surv-MDR and is comparable with that of Cox-MDR, but is very sensitive to the censoring fraction.