• 산업경영시스템학회지
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• 제24권63호
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• pp.45-54
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• 2001

The process capability indices have been widely used in manufacturing industries to provide numerical measures of process potential and performance. This study is concerned with process controls and adjustments by incapability index $C_{pp}$ and its sub-indices. A monitoring for $\^{C}_{pp}$ would provide a convenient way to monitor changes on process capability after statistical control is established, since $C_{pp}$ simultaneously measures process variability and centering. Further, we can separate charting of process location and variability by sub-indices of $C_{pp}$, ($C_{ia}$, $C_{ip}$), without returning to $\={x}$-R chart, even though an out-of-control signals on $\^{C}_{pp}$ control chart is found.

• Current Optics and Photonics
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• 제1권5호
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• pp.551-555
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• 2017

Tissue optics is a well-established and extensively studied area. In the last decades, Monte Carlo simulation (MCS) has been one of the standard tools for simulation of light propagation in turbid media. The utilization of parallel processing exhibits dramatic increase in the speed of MCS's of photon migration. Some calculations based on MCS can be completed within a few seconds. Since the MCS's have the potential to become a real time calculation method, a dynamic accuracy estimation, which is also known as history by history statistical estimators, is required in the simulation code to automatically terminate the MCS as the results' accuracy achieves a high enough level. In this work, spatial and time-domain GPU-based MCS, adopting the dynamic accuracy estimation, are performed to calculate the light dose/reflectance in homogeneous and heterogeneous tissue media. This dynamic accuracy estimation can effectively derive the statistical error of optical dose/reflectance during the parallel Monte Carlo process.

• Communications for Statistical Applications and Methods
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• 제13권2호
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• pp.389-407
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• 2006

Extreme value theory has been used widely in many areas of science and engineering to deal with the assessment of extreme events which are rare but have catastrophic consequences. The potential of extreme value theory has only been recognized recently in finance area. In this paper, we provide an overview of extreme value theory for estimating and assessing value at risk and expected shortfall which are the methods for modelling and measuring the extreme financial risks. We illustrate that the approach based on extreme value theory is very useful for estimating tail related risk measures through backtesting of an empirical data.

• Communications for Statistical Applications and Methods
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• 제11권3호
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• pp.619-629
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• 2004

Binomial group testing or composite sampling is often used to estimate the proportion, p, of positive(infects, defectives) in a population when that proportion is known to be small; the potential benefits of group testing over one-at-a-time testing are well documented. The literature has focused on maximum likelihood estimation. We provide two Bayes estimators and compare them with the MLE. The first of our Bayes estimators uses an uninformative Uniform (0, 1) prior on p; the properties of this estimator are poor. Our second Bayes estimator uses a much more informative prior that recognizes and takes into account key aspects of the group testing context. This estimator compares very favorably with the MSE, having substantially lower mean squared errors in all of the wide range of cases we considered. The priors uses a Beta distribution, Beta ($\alpha$, $\beta$), and some advice is provided for choosing the parameter a and $\beta$ for that distribution.

• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.431-443
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• 2020

The K-means clustering algorithm has had successful application in sufficient dimension reduction. Unfortunately, the algorithm does have reproducibility and nestness, which will be discussed in this paper. These are clear deficits for the K-means clustering algorithm; however, the hierarchical clustering algorithm has both reproducibility and nestness, but intensive comparison between K-means and hierarchical clustering algorithm has not yet been done in a sufficient dimension reduction context. In this paper, we rigorously study the two clustering algorithms for two popular sufficient dimension reduction methodology of inverse mean and clustering mean methods throughout intensive numerical studies. Simulation studies and two real data examples confirm that the use of hierarchical clustering algorithm has a potential advantage over the K-means algorithm.

• Architectural research
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• 제14권2호
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• pp.45-56
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• 2012

The high rate of urban crime is a main issue that needs to be dealt with in this high-tech society. With the rapid increase of urban crime, research has mainly focused on topics either on a global or a local scale, such as cities or communities and houses or buildings, without reliable observational data. This study makes the best use of the nationwide surveys carried out by Korean government agencies for the analysis of urban crime patterns and factors in major Korean cities. The aims of this research are threefold: understanding the relationship between urban crime patterns and socio-economic differences in cities, determining the effect of residence types on the urban crime patterns; and uncovering potential influential factors of a crime victim's individual characteristics. The statistical methods used for the analysis of social statistical data are as follows: simple regression, logistic regression, one-way ANOVA and post-hoc test. This research found that the patterns of urban crime rate in cities have a certain tendency toward the cities' socio-economic and geographical differences. The residence type is an influential factor showing a close relation to the crime rate. Personal issues, such as the types of occupation, education, marriage, etc., are directly relevant to victims of crime.

• 응용통계연구
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• 제24권1호
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• pp.1-10
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• 2011

본 연구는 포트폴리오 이론에 입각해 위험을 최소화하기 위한 투자의 국제적 분산 가능성에 대해 통계적으로 검정해 보았다. 국내외 주요 주식시장 간 동적 상호의존 관계와 구조변화를 검색하는 접근방식을 적용시켜 본 결과 아시아 외환위기에 따른 공통요인들의 존재로 인해 각 주식시장의 독자적 변동이 제약을 받아 투자의 다각화에 따른 수익이 제한되는 것으로 나타났다. 투자 다변화 여건이 조성되는 시기는 주식시장 간 동조화 현상이 약화된 이후로 판명되며, 검정결과는 당시 해외투자와 펀드판매의 증가 시기 및 시장성향의 현실을 그대로 반영한다.

• 한국가스학회지
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• 제10권4호
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• pp.29-33
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• 2006

화학공정 설계에서 공정의 위험성 판단은 중요한 부분이다. 실제 화학공정에 사용되는 가연성 물질의 화재 및 폭발 위험성을 판단하는 인화점에 대한 예측은 그 방법 중의 하나이다. 본 연구에서는 2성분계 가연성 물질의 인화점에 대한 실험 자료를 이용하여 다변량 통계 분석법(partial least squares(PLS), quadratic partial least squares(QPLS))을 이용하여 2성분계 혼합물의 인화점을 예측하였고, 기존의 Raoult의 법칙과 Van Laar 식에 의한 예측값과 비교해 보았다.

• ETRI Journal
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• 제25권5호
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• pp.401-406
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• 2003

A biometric system determines the identity of a person by measuring physical features that can distinguish that person from others. Since biometric features have many variations and can be easily corrupted by noises and deformations, it is necessary to apply machine learning techniques to treat the data. When applying the conventional machine learning methods in designing a specific biometric system, however, one first runs into the difficulty of collecting sufficient data for each person to be registered to the system. In addition, there can be an almost infinite number of variations of non-registered data. Therefore, it is difficult to analyze and predict the distributional properties of real data that are essential for the system to deal with in practical applications. These difficulties require a new framework of identification and verification that is appropriate and efficient for the specific situations of biometric systems. As a preliminary solution, this paper proposes a simple but theoretically well-defined method based on a statistical test theory. Our computational experiments on real-world data show that the proposed method has potential for coping with the actual difficulties in biometrics.

• 한국물환경학회지
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• 제25권4호
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• pp.494-501
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• 2009

Probabilistic Ecological risk assessment (PERA) is extensive approach to qualify and quantify risk on the multi species based on species sensitivity distribution (SSD). As a while, deterministic ecological risk assessment (DERA) considers the comparison of predicted no-effect concentration (PNEC) and predicted exposure concentration (PEC). DERA is used to determine if there is potential risk or no risk, and it doesn't consider the nature variability and the species sensitivity. But PERA can be more realistic and reasonable approach to estimate likelihood or risk. In this study, we compared PERA used in developed countries, and proposed PERA applicable for the Korean water environment. Taxonomic groups were classified as "class" level including Actinopterygill, Branchiopoda, Chlorophyceae, Maxillapoda, Insects, Bivalvia, Gastropoda, Secernentea, Polychaeta, Monocotyldoneae, and Chanophyceae in this study. Statistical extrapolation method (SEM), statistical extrapolation method $_{acutechronicratio}$ ($SEM_{ACR}$) and assessment factor method (AFM) were used to calculate the ecological protective concentration based on qualitative and quantitative levels of taxonomic toxicity data. This study would be useful to establish the PERA for the protection of aquatic ecosystem in Korea.