• 대한기계학회논문집A
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• 제34권11호
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• pp.1691-1696
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• 2010

설계단계에서 시스템의 불확실성을 반영하려는 노력이 다양하게 이루어지고 있으며, 강건 최적설계 혹은 신뢰도 기반 최적설계는 이에 대한 대표적인 설계 방법론이다. 이러한 최적화 수식에는 성능함수의 평균, 표준편차와 확률제한조건이 목적함수와 제한조건으로 주로 활용된다. 그러므로, 이러한 통계적 특성치를 효과적으로 계산하는 것은 필수적이며, 더 나아가 최적화 과정에서 비선형 계획법이 일반적으로 활용되므로 민감도가 반드시 필요하다. 본 연구에서는 통계적 모멘트와 확률제한조건에 대해 적분 형태로 정의되는 민감도 수식을 비정규 분포로 확장하고자 한다. 얻어진 민감도 해석 결과는 통계적 모멘트와 손상확률이 설계점에서 계산된 경우, 민감도를 얻기 위해 추가로 성능함수를 계산할 필요가 없음을 보여주므로 효율성 측면에서 우수하다. 그러나, 민감도 수식이 성능함수와 확률밀도함수의 미분과정에서 얻어지는 함수의 곱으로 정의되므로, 동일한 수치적분 방법이 적용되는 경우 민감도 해석 결과는 통계적 모멘트 결과의 정확도에 미치지 못할 가능성이 있다.

• Communications for Statistical Applications and Methods
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• 제14권2호
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• pp.281-286
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• 2007

Cook's distance is generalized to the multiple linear regression with linear constraints on regression coefficients. It is used for identifying influential observations in constrained regression models. A numerical example is provided for illustration.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.47-54
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• 2000

This article is concerned with the algorithm for the Chebyshev estimation with/without linear equality and/or inequality constraints. The algorithm employs a linear scaling transformation scheme to reduce the computational burden which is induced when the data set is quite large. The convergence of the proposed algorithm is proved. And the updating and orthogonal decomposition techniques are considered to improve the computational efficiency and numerical stability.

• 산업경영시스템학회지
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• 제39권1호
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• pp.130-139
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• 2016

The purpose of this paper is to analyze the problems and the sources of defective products and draw improvement plans in a small plastic boat manufacturing process using TOC (Theory Of Constraints) and statistical analysis. TOC is a methodology to present a scheme for optimization of production process by finding the CCR (Capacity Constraints Resource) in the organization or the all production process through the concentration improvement activity. In this paper, we found and reformed constraints and bottlenecks in plastic boat manufacturing process in the target company for less defect ratio and production cost by applying DBR (Drum, Buffer, Rope) scheduling. And we set the threshold values for the critical process variables using statistical analysis. The result can be summarized as follows. First, CCRs in inventory control, material mix, and oven setting were found and solutions were suggested by applying DBR method. Second, the logical thinking process was utilized to find core conflict factors and draw solutions. Third, to specify the solution plan, experiment data were statistically analyzed. Data were collected from the daily journal addressing the details of 96 products such as temperature, humidity, duration and temperature of heating process, rotation speed, duration time of cooling, and the temperature of removal process. Basic statistics and logistic regression analysis were conducted with the defection as the dependent variable. Finally, critical values for major processes were proposed based on the analysis. This paper has a practical importance in contribution to the quality level of the target company through theoretical approach, TOC, and statistical analysis. However, limited number of data might depreciate the significance of the analysis and therefore it will be interesting further research direction to specify the significant manufacturing conditions across different products and processes.

• 응용통계연구
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• 제27권6호
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• pp.909-922
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• 2014

부등제한 조건 (>,<,=)과 관련된 베이지안 추론에서 다음의 세 가지 주제에 대하여 기존의 연구와 최근의 연구동향 그리고 추후 연구주제에 대하여 살펴보았다 : ⅰ) 모수에 대한 여러 부등제한 조건들의 비교, ⅱ) 모수에 부등제한 조건을 부여하는 것이 타당하다고 할 때 모수의 동등성에 관한 동시 다중 검정, ⅲ) 순서적 범주형 변수에 대한 분할표에서 스코어 모수에 순서적 부등제한 조건을 가정 할 때 스코어 모수의 동등성에 대한 다중 검정.

• 대한기계학회논문집A
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• 제26권12호
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• pp.2483-2491
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• 2002

This study presents an efficient method for robust optimal design. In order to avoid the excessive evaluations of the exact performance functions, two-point diagonal quadratic approximation method is employed for approximating them during optimization process. This approximation method is one of the two point approximation methods. Therefore, the second order sensitivity information of the approximated performance functions are calculated by an analytical method. As a result, this enables one to avoid the expensive evaluations of the exact $2^{nd}$ derivatives of the performance functions unlike the conventional robust optimal design methods based on the gradient information. Finally, in order to show the numerical performance of the proposed method, one mathematical problem and two mechanical design problems are solved and their results are compared with those of the conventional methods.

• 천문학회보
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• 제36권1호
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• pp.46.1-46.1
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• 2011

New statistical method is proposed to coherently combine Baryon Acoustic Oscillation statistics (BAO) and peculiar velocity measurements exploiting decomposed density--density and velocity--velocity spectra in real space from the observed redshift distortions in redshift space, 1) to achieve stronger dark energy constraints, sigma(w)=0.06 and sigma(w_a)=0.20, which are enhanced from BAO or velocity measurements alone, and 2) to cross--check consistency of dark energy constraints from two different approaches; BAO as geometrical measurements and peculiar velocity as large scale structure formation observables.

• Communications for Statistical Applications and Methods
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• 제25권2호
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• pp.131-157
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• 2018

We propose a robust event date model to estimate the date of a target event by a combination of individual dates obtained from archaeological artifacts assumed to be contemporaneous. These dates are affected by errors of different types: laboratory and calibration curve errors, irreducible errors related to contaminations, and taphonomic disturbances, hence the possible presence of outliers. Modeling based on a hierarchical Bayesian statistical approach provides a simple way to automatically penalize outlying data without having to remove them from the dataset. Prior information on individual irreducible errors is introduced using a uniform shrinkage density with minimal assumptions about Bayesian parameters. We show that the event date model is more robust than models implemented in BCal or OxCal, although it generally yields less precise credibility intervals. The model is extended in the case of stratigraphic sequences that involve several events with temporal order constraints (relative dating), or with duration, hiatus constraints. Calculations are based on Markov chain Monte Carlo (MCMC) numerical techniques and can be performed using ChronoModel software which is freeware, open source and cross-platform. Features of the software are presented in Vibet et al. (ChronoModel v1.5 user's manual, 2016). We finally compare our prior on event dates implemented in the ChronoModel with the prior in BCal and OxCal which involves supplementary parameters defined as boundaries to phases or sequences.

• Asian-Australasian Journal of Animal Sciences
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• 제31권9호
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• pp.1381-1386
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• 2018

Animal experiments are essential to the study of animal nutrition. Because of the large variations among individual animals and ethical and economic constraints, experimental designs and statistical analyses are particularly important in animal experiments. To increase the scientific validity of the results and maximize the knowledge gained from animal experiments, each experiment should be appropriately designed, and the observations need to be correctly analyzed and transparently reported. There are many experimental designs and statistical methods. This editorial does not aim to review and present particular experimental designs and statistical methods. Instead, we discuss some essential elements when designing an animal experiment and conducting statistical analyses in animal nutritional studies and provide guidelines for submitting a manuscript to the Asian-Australasian Journal of Animal Sciences for consideration for publication.

• 응용통계연구
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• 제24권4호
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• pp.721-733
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• 2011

We consider the state price densities that are implicit in financial asset prices. In the pricing of an option, the state price density is proportional to the second derivative of the option pricing function and this relationship together with no arbitrage principle imposes restrictions on the pricing function such as monotonicity and convexity. Since the state price density is a proper density function and most of the shape constraints are caused by this, we propose to estimate the state price density directly by specifying candidate densities in a flexible nonparametric way and applying methods of regularization under extra constraints. The problem is easy to solve and the resulting state price density estimates satisfy all the restrictions required by economic theory.