• Communications for Statistical Applications and Methods
• /
• v.30 no.4
• /
• pp.355-368
• /
• 2023

This article introduces the R package ELCIC (https://cran.r-project.org/web/packages/ELCIC/index.html), which provides an empirical likelihood-based information criterion (ELCIC) for model selection that includes, but is not limited to, variable selection. The empirical likelihood is a semi-parametric approach to draw statistical inference that does not require distribution assumptions for data generation. Therefore, ELCIC is more robust and versatile in the context of model selection compared to the currently existing information criteria. This paper illustrates several applications of ELCIC, including its use in generalized linear models, generalized estimating equations (GEE) for longitudinal data, and weighted GEE (WGEE) for missing longitudinal data under the mechanisms of missing at random and dropout.

• Journal of Information Technology Services
• /
• v.8 no.2
• /
• pp.1-22
• /
• 2009

Recently, improving service quality for customer satisfaction is one of the most important issues and the task for the growth of company. Furthermore, plenty studies are going on progress to develop service quality in IT industry. There have been so many researches of product quality on package software but yet the service quality of package software has been rarely studied before. Thus, the purpose of this study is to formulate a scheme on how to enhance the competitivity of package software company by analyzing the impacts of these two factors on the customer satisfaction, Word-of-Mouth intention and the reuse intention. The study models have been designed and the hypotheses have been made through the examination of the precedent literature about package software product and service quality. A questionnaire survey was performed to collect information, and the unit of analysis was a person who used package software. This study used the statistical technique such as regression analysis. This study may be utilized as basic data for building marketing strategies when package software companies offer service to customers.

• The Journal of Information Systems
• /
• v.25 no.4
• /
• pp.121-139
• /
• 2016

Purpose In this study, we propose the special purposed R package named ""new_Noun()" to process nonstandard texts appeared in various social networks. As the Big data is getting interested, R - analysis tool and open source software is also getting more attention in many fields. Design/methodology/approach With more than 9,000 R packages, R provides a user-friendly functions of a variety of data mining, social network analysis and simulation functions such as statistical analysis, classification, prediction, clustering and association analysis. Especially, "KoNLP" - natural language processing package for Korean language - has reduced the time and effort of many researchers. However, as the social data increases, the informal expressions of Hangeul (Korean character) such as emoticons, informal terms and symbols make the difficulties increase in natural language processing. Findings In this study, to solve the these difficulties, special algorithms that upgrade existing open source natural language processing package have been researched. By utilizing the "KoNLP" package and analyzing the main functions in noun extracting command, we developed a new integrated noun processing package "new_Noun()" function to extract nouns which improves more than 29.1% compared with existing package.

• Journal of the Ergonomics Society of Korea
• /
• v.18 no.2
• /
• pp.57-69
• /
• 1999

The primary objective of this research was to suggest the design dimensions of automotive seating package that has an important effect upon seating package design. To conduct the research, a set of manikin dimensions that are representative for Korean was determined by using a statistical scheme. With these dimensions, we generated nine manikins for male and female, respectively. Also, the preferred driving posture was investigated using the experimental setup. To find each joint angle for subjects, a driving monitoring system was developed and a three dimensional motion analysis system was employed. The joint angle for the subject was established and compared with related literature. With the generated manikins and each joint angle, the driving posture was simulated by using SAFEWORK that is a program to generate manikins. The positions and adjustable ranges from the accelerator heel point to the hip point and the steering wheel center point that are important variables in order to design seating package were suggested. Further research is needed to determine the seating package dimensions three dimensionally.

• Korean Journal of Oriental Medicine
• /
• v.18 no.2
• /
• pp.55-64
• /
• 2012

Objectives: This study was performed to review the use of statistical analysis methods for the Traditional Korean Medicine studies listed on the Korea Citation Index from 1999 to 2008. Methods: A total of 4217 studies published on four journals of Traditional Korean Medicine were screened and 2682 articles using statistical methods were selected for the review. The selected studies were analysed according to their published year, statistical method and statistical package for use. Results: Statistical methods were used steadily in 64.6% of the articles after 2001, the most used statistical methods(57%) were mean difference comparison between 2 groups. The number of statistical methods mostly used in one article was identified as one in 1931 articles (72.0%). Duncan (36.8%) and Tukey (26.5%) were used for the ANOVA post hoc analysis. SPSS was most frequently used 68% out of Statistical package programs.(the number of mean difference comparison among more than 3 groups was continuously increasing and that makes post hoc being used. skills of statistical methods need to be diversified.) Conclusion: The interest on the proper use of statistical analysis in the research is increasing. This study will contribute to the Evidence-based Teaching on research methodology in Traditional Korean Medicine.

• The Korean Journal of Applied Statistics
• /
• v.27 no.3
• /
• pp.487-500
• /
• 2014

The elementary school curriculum includes some statistical concepts and many graphical methods. However, statistical concepts are difficult to understand; consequently, many of those graphs and numerical summaries are obtained by hand. We develop an intuitive statistics education package called Tong-Gramy focused on 5-8 graders to help students and teachers study statistics. This software covers numerical and graphical statistics that appear in 5-8 graders' textbooks. The graphs provided are dynamically linked to data and every graph is linked to every datum. The graphs of Tong-Gramy are dynamic graphs and morphing technology is used where applicable.

• Communications for Statistical Applications and Methods
• /
• v.12 no.1
• /
• pp.61-69
• /
• 2005

In conducting the analysis of variance for the split-plot design using the statistical package SPSS, users including statisticians are faced with difficulties because of no appropriate example in the SPSS applications guide book. In this paper, therefore, we present an analysis of variance procedure for the split-plot design using SPSS syntax window.

• Korean Journal of Oriental Medicine
• /
• v.13 no.2 s.20
• /
• pp.121-125
• /
• 2007

Background and Purpose : The purpose of this study was done to investigate what kinds of statistical techniques have been used to analyze data from oriental medicine research Methods : 135 original articles which used statistical techniques in their data analysis were selected from the articles published in The Journal of Korea Institute of Oriental Medicine(JKIOM) between 1995 to 2007. Results : Among 135 articles, 59 articles used descriptive statistics while 76 articles used inferential statistics for data analysis. For that 76 articles, two-sample t-test(33 articles), analysis of variance(29 articles), regression(9 articles), chi-square test(5 articles), nonparametic test(4 articles), Fisher's exact test(3 articles), and other test(9 articles) were chosen to analyze the data. SAS and SPSS statistical softwares(82.50%) were mostly used to analyze the data. Nonparametic tests were used to 4 articles(6.97%) of 67 articles and parametic tests were used to 63 articles(93.03%) of 67 articles. Among 29 articles used analysis of variance, duncan(8 articles), dunnet(4 articles), bonferroni(4 articles), turkey(3 articles), scheff(1 article) were used to do multiple comparison. 9 articles did not carry out the multiple comparison. Conclusions : It was found that the frequencies of statistical package used and statistical analysis used were not much by now. High level statistical analyses were not used most for oriental medicine research.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.15 no.4
• /
• pp.531-539
• /
• 1996

The research for the classification of the artificial defects in welding parts is performed using the pattern recognition technology of ultrasonic signal. The signal pattern recognition package including the user defined function is developed to perform the digital signal processing, feature extraction, feature selection and classifier selection. The neural network classifier and the statistical classifiers such as the linear discriminant function classifier and the empirical Bayesian classifier are compared and discussed. The pattern recognition technique is applied to the classification of artificial defects such as notchs and a hole. If appropriately learned, the neural network classifier is concluded to be better than the statistical classifiers in the classification of the artificial defects.

• Communications for Statistical Applications and Methods
• /
• v.18 no.3
• /
• pp.319-331
• /
• 2011

In this paper, we propose automatic procedures for the model selection of various univariate time series data. Automatic model selection is important, especially in data mining with large number of time series, for example, the number (in thousands) of signals accessing a web server during a specific time period. Several methods have been proposed for automatic model selection of time series. However, most existing methods focus on linear time series models such as exponential smoothing and autoregressive integrated moving average(ARIMA) models. The key feature that distinguishes the proposed procedures from previous approaches is that the former can be used for both linear time series models and nonlinear time series models such as threshold autoregressive(TAR) models and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA-GARCH) models. The proposed methods select a model from among the various models in the prediction error sense. We also provide an R package autots that implements the proposed automatic model selection procedures. In this paper, we illustrate these algorithms with the artificial and real data, and describe the implementation of the autots package for R.