• Title/Summary/Keyword: statistical analysis.

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Review of Confirmatoty Data Analysis and Exploratory Data Analysis in Statistical Quality Control, Design of Experiment and Reliability Engineering (SQC, DOE 및 RE에서 확증적 데이터 분석(CDA)과 탐색적 데이터 분석(EDA)의 고찰)

  • Choi, Sung-Woon
    • Proceedings of the Safety Management and Science Conference
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    • 2010.04a
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    • pp.253-258
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    • 2010
  • The paper reviews the methodologies of confirmatory data analysis(CDA) and exploratory data analysis(EDA) in statistical quality control(SQC), design of experiment(DOE) and reliability engineering(RE). The study discusses the properties of flexibility, openness, resistance and reexpression for EDA.

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Arrow Diagrams for Kernel Principal Component Analysis

  • Huh, Myung-Hoe
    • Communications for Statistical Applications and Methods
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    • v.20 no.3
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    • pp.175-184
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    • 2013
  • Kernel principal component analysis(PCA) maps observations in nonlinear feature space to a reduced dimensional plane of principal components. We do not need to specify the feature space explicitly because the procedure uses the kernel trick. In this paper, we propose a graphical scheme to represent variables in the kernel principal component analysis. In addition, we propose an index for individual variables to measure the importance in the principal component plane.

Higher-order solutions for generalized canonical correlation analysis

  • Kang, Hyuncheol
    • Communications for Statistical Applications and Methods
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    • v.26 no.3
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    • pp.305-313
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    • 2019
  • Generalized canonical correlation analysis (GCCA) extends the canonical correlation analysis (CCA) to the case of more than two sets of variables and there have been many studies on how two-set canonical solutions can be generalized. In this paper, we derive certain stationary equations which can lead the higher-order solutions of several GCCA methods and suggest a type of iterative procedure to obtain the canonical coefficients. In addition, with some numerical examples we present the methods for graphical display, which are useful to interpret the GCCA results obtained.

A Statistical Expert System for Simulation Analysis-Revised (시뮬레이션의 통계적 분석을 위한 전문가 시스템)

  • Park, Young-Hong
    • IE interfaces
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    • v.7 no.1
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    • pp.81-91
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    • 1994
  • Simulation is one of the most widely used techniques in operations research and management science, but there are several impediments to even wider acceptance and use of simulation. One of the more significant limitations is the dependence of simulation on statistical methodology. This research identifies eighteen different statistical issues in simulation methodology and develops an expert system which could through interactive dialog with simulation analysts offer advice on statistical approaches which might be used to deal with particular issues and to accomplish required statistical computations. This research revises the previous study published in Simulation by incorporating additional statistical issues in the expert system to enhance its performance in analyzing a given simulation problem with statistical methodologies. An overview of the revised system is given and illustrations of the capabilities of the system are presented.

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STATISTICAL EVIDENCE METHODOLOGY FOR MODEL ACCEPTANCE BASED ON RECORD VALUES

  • Doostparast M.;Emadi M.
    • Journal of the Korean Statistical Society
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    • v.35 no.2
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    • pp.167-177
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    • 2006
  • An important role of statistical analysis in science is interpreting observed data as evidence, that is 'what do the data say?'. Although standard statistical methods (hypothesis testing, estimation, confidence intervals) are routinely used for this purpose, the theory behind those methods contains no defined concept of evidence and no answer to the basic question 'when is it correct to say that a given body of data represent evidence supporting one statistical hypothesis against another?' (Royall, 1997). In this article, we use likelihood ratios to measure evidence provided by record values in favor of a hypothesis and against an alternative. This hypothesis is concerned on mean of an exponential model and prediction of future record values.

Development of a Simplified Statistical Methodology for Nuclear Fuel Rod Internal Pressure Calculation

  • Kim, Kyu-Tae;Kim, Oh-Hwan
    • Nuclear Engineering and Technology
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    • v.31 no.3
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    • pp.257-266
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    • 1999
  • A simplified statistical methodology is developed in order to both reduce over-conservatism of deterministic methodologies employed for PWR fuel rod internal pressure (RIP) calculation and simplify the complicated calculation procedure of the widely used statistical methodology which employs the response surface method and Monte Carlo simulation. The simplified statistical methodology employs the system moment method with a deterministic approach in determining the maximum variance of RIP The maximum RIP variance is determined with the square sum of each maximum value of a mean RIP value times a RIP sensitivity factor for all input variables considered. This approach makes this simplified statistical methodology much more efficient in the routine reload core design analysis since it eliminates the numerous calculations required for the power history-dependent RIP variance determination. This simplified statistical methodology is shown to be more conservative in generating RIP distribution than the widely used statistical methodology. Comparison of the significances of each input variable to RIP indicates that fission gas release model is the most significant input variable.

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Selections and applications of statistical packages for personal computers (개인용 컴퓨터에서의 통계페키지의 선택과 활용)

  • 김병천
    • The Korean Journal of Applied Statistics
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    • v.1 no.1
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    • pp.75-90
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    • 1987
  • Statistical data analysis using the statisticaal packages can be performed on the personal computers. But it is not easy to select a personal computer in which statisticians could run statistical packages. The paper discusses some of the minimum requirements of the personal computers to use statistical packages and how to choose good statistical packages with better numerical results and introduces the statistical packages which are available in the personal computers.

Statistical Analysis of Transfer Function Models with Conditional Heteroscedasticity

  • Baek, J.S.;Sohn, K.T.;Hwang, S.Y.
    • Journal of the Korean Statistical Society
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    • v.31 no.2
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    • pp.199-212
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    • 2002
  • This article introduces transfer function model (TFM) with conditional heteroscedasticity where ARCH concept is built into the traditional TFM of Box and Jenkins (1976). Model building strategies such as identification, estimation and diagnostics of the model are discussed and are illustrated via empirical study including simulated data and real data as well. Comparisons with the classical TFM are also made.

On-Line Analytical Processing and Research Problems for Statisticians

  • Ahn, JeongYong;Han, Kyung Soo
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.457-463
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    • 2000
  • Recently, statistical analysis tools have been changed to the applications on the World Wide Web that access data stored in databases. On-line analytical processing(OLAP) is a class of technologies that give users statistical information with multidimensional views of data in databases. In this paper, we introduce the concept and requisites of OLAP system, and we propose some research issues.

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New Paradigm in Statistical Education

  • Lee, Jae-Woo;Lee, Jea-Young
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.05a
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    • pp.49-55
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    • 2003
  • Korea has the most level of Internet Infrastructure in the world. But, in the educational aspect, it does not have an enough foundation about Statistical Education. In this paper we consider the methods of activation about statistics. Also, we present what is the Enterprise Guide and what does it have characteristics as statistical analysis tool from educational point of view. And we suggest a new paradigm in statistical education.

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