• 항공우주시스템공학회지
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• 제10권3호
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• pp.63-69
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• 2016

The properties of composite materials, when compared to those of metallic materials, are highly variable due to many factors including the batch-to-batch variability of raw materials, the prepreg manufacturing process, material handling, part-fabrication techniques, ply-stacking sequences, environmental conditions, and test procedures. It is therefore necessary to apply reliable statistical-analysis techniques to obtain the design allowables of composite materials. A new composite-material qualification process has been developed by the Advanced General Aviation Transport Experiments (AGATE) consortium to yield the lamina-design allowables of composite materials according to standardized coupon-level tests and statistical techniques; moreover, the generated allowables database can be shared among multiple users without a repeating of the full qualification procedure by each user. In 2005, NASA established the National Center for Advanced Materials Performance (NCAMP) with the purpose of refining and enhancing the AGATE process to a self-sustaining level to serve the entire aerospace industry. In this paper, the statistical techniques and procedures for the generation of the allowables of aerospace composite materials will be discussed with a focus on the pooling-across-environments method.

• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.337-344
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• 1998

통계청에서 조사 발표한 '96가구소비실태조사의 지역결과 자료에 대한 통계적 신뢰도를 분석하며, 전국 혹은 넓은 지역을 대상으로 하는 조사에서 소지역 통계의 오차를 줄여 신뢰도를 높이는 추정방법을 제안한다.

• International Journal of Safety
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• 제6권2호
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• pp.13-16
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• 2007

This study focuses on the trends and issues of improving safety management of elevators in Korea. Frequency and severity of accidents in relation to conditional pass in periodic inspection, maintenance, market surveillance are analyzed based on the statistical data and social cost due to a variety of related fields in managing elevator safety was estimated first. The results of statistical analysis performed in this study will provide logical basis and future direction for improving the safety management system. The role of certification and supervision is particularly addressed to reduce the related accidents and the social cost. The effectiveness of such procedures can be found from the results of simple statistical analysis.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.63-68
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• 2003

One of the widely accepted assumptions in many statistical problem is that the underlying distribution is symmetric. Though a large number of nonparametric test are available in the literature for this problem, very few procedures focuses on the distributional structure when the symmetry assumption is rejected. Yanagimoto and Sibuya (1972) provided the various types of asymmetric distributional structure, positive biasedness, namely. In this paper we consider the test of symmetry against several new positive biasedness restrictions which are stronger than Yanagimoto and Sibuya's type II bias but weaker than type IV (III) bias.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.589-601
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• 1996

Geometric approach to extend the classical two-set theory of canonical correlation analysis to three or more sets is considered. It provides statistical graphs to represent the data in a low dimensional space. Procedures are developed for computing the canonical variables and the corresponding properties are investigated. The solution is equivalent to that of the usual problem in the case of two sets. Goodness-of-fit of the proposed plots is studied and a numerical example is included.

• Communications for Statistical Applications and Methods
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• 제5권1호
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• pp.239-263
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• 1998

In this paper, we consider a multistate survival model which incorporates covariates and contains two illness states and two death states. The underlying stochastic process is assumed to follow nonhomogeneous Markov process. The estimates of survival, transition and competing risks probabilities are given via the methods of partial likelihood and nonparametric maximum likelihood. Our discussion is based on the statistical theory of counting process. An illustration is given to the data of patients in a heart transplant program. The goodness of fit procedures are also discussed to check the adequacy of the model.

• 간호행정학회지
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• 제13권2호
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• pp.199-207
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• 2007

Purpose: Clinical characteristics and medical cost were analyzed according to the surgical procedures for intertrochanteric fracture in aged patients to assess the appropriateness of treatment expense and to find possibility of reducing the medical cost. Method: Variable for the statistical analysis were; the clinical characteristics, medical cost according to the surgical procedures, the treatment success rate, the total medical expense, and the average expense per case. SAS Package Version 8.02. was used to analyze the relevant data. Results: Operative procedures differ significantly according to the gender and by the location of institution. Only significant clinical variables according to the operative procedure were duration of general anesthesia and amount of blood transfusion. Average cost per treatment was the highest in the bipolar hemiarthroplasty followed by the gamma nail and hip compressing screw. Average cost for bipolar hemiarthroplasty was significantly higher than other surgical procedures. Conclusions: The difference in hospital costs for treatment of intertrochanteric fracture originates from the utilized surgical procedures, mostly by the materials used. The method of surgical treatment should be carefully determined by the purpose of the surgery, in order to improve the quality of medical care and also to reduce the hospital cost.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.1-14
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• 2020

Investigations of biosimilarity between reference drugs and test drugs required statistical tests; in addition, statistical tests to evaluate biosimilarity have been recently proposed. Ordinal outcome data has been observed in research; however, appropriate statistical tests to deal with ordinal endpoints for biosimilar have not yet been proposed. This paper extends existing design for ordinal endpoints. Using measure of nominal-ordinal association and relative distances between drugs are defined so that testing procedures are developed. Through simulation studies, we investigate type I error rate and power to show the performance of our suggested method. Furthermore, a comparison between the statistical tests and other designs is proviede to show significance of ordinal endpoints.

• Communications for Statistical Applications and Methods
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• 제18권3호
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• pp.319-331
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• 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.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.713-727
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• 2005

Among different regression approaches, nonparametric procedures perform well under different conditions. In practice it is very hard to identify which is the best procedure for the data at hand, thus model combination is of practical importance. In this paper, we focus on one dimensional regression with fixed design. Polynomial regression, local regression, and smoothing spline are considered. The data are split into two parts, one part is used for estimation and the other part is used for prediction. Prediction performances are used to assign weights to different regression procedures. Simulation results show that the combined estimator performs better or similarly compared with the estimator chosen by cross validation. The combined estimator generates a similar risk to the best candidate procedure for the data.