• 한국항공우주학회지
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• 제49권6호
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• pp.521-528
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• 2021

위협평가가 끝난 공중항적에 대해 적절한 대응무기를 할당하기 위해서는 교전예상지점을 고려하여 교전적합성을 평가하는 것이 필요하다. 논문에서는 공중항적이 교전공간을 통과할 때 공중항적의 상대거리, 접근방위각 및 고도 등 다변량 속성정보를 가지고 베이지안 정리를 적용하여 교전공간내 위치에 따른 격추확률을 계산하는 방법을 제시하였다. 계산결과 교전공간내에서의 각 지점별 격추확률값의 분포형태는 최적의 예상요격지점을 기준으로 다변량 정규분포를 따르고 있음을 확인하였고, 계산된 격추확률값은 교전공간을 통과하는 공중항적의 교전가능성 평가에 적용가능할 것으로 기대된다.

• 한국자기공명학회논문지
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• 제16권1호
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• pp.46-66
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• 2012

Metabolomic studies using human urine have shown that human metabolism is altered by a variety of environmental, cultural, and physiological factors. Comprehensive information about normal human metabolite profiles is necessary for accurate clinical diagnosis of disease and for disease prevention and treatment. In this study, metabolite correlation analyses, using $^1H$ nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistics, were performed on human urine to compare metabolic differences based on gender and/or obesity in healthy human subjects. First, we applied partial least squares discriminant analysis to the NMR spectral data set to verify the data's ability to discriminate by gender and obesity. Then, the differences in metabolite-metabolite correlation between male and female, and between normal and high body mass index (obese) subjects were investigated through pairwise correlations. Creatine and several metabolites, including isoleucine, trans-aconitate, and trimethylamine N-oxide (TMAO), exhibited different quantitative relationships depending on gender. Dimethylamine had a different correlation with glycine and TMAO, based on gender. The correlation of TMAO with amino acids was considerably lower in obese, compared to normal, subjects. We expect that the results will shed light on the metabolic pathways of healthy humans and will assist in the accurate diagnosis of human disease.

• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.511-521
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• 2020

In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.919-929
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• 2013

We compared two basic methods, combine-accumulate method and accumulate-combine method, using the past quality information in multivariate quality control procedure for monitoring mean vector of multivariate normal process. When small or moderate shifts have occurred, accumulate-combine method yields smaller average run length (ARL) and average time to signal (ATS) than combine-accumulate method. On the other hand, we have found from our numerical results that combine-accumulate method has better performances in terms of switching behavior than accumulate-combine method. In industry, a quality engineer could select one of the two method under the comprehensive consideration about the required time to signal, switching behavior, and other physical factors in the production process.

• 통합자연과학논문집
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• 제5권3호
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• pp.151-156
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• 2012

Because of the equivalence between control chart procedures and hypothesis testing, we propose to use likelihood ratio test (LRT) statistic $Z_i^2$ as the multivariate control statistic for simultaneous monitoring means of the multivariate normal process. Properties and comparisons of the proposed control charts are explored and conducted for matched fixed sampling interval (FSI) and variable sampling interval (VSI) with two sampling interval charts. The result of numerical comparisons shows that EWMA chart with two sampling interval procedure is more efficient than the corresponding FSI chart for small or moderate changes. When large shift of the process has occurred, we also found that Shewhart chart is more efficient than EWMA chart.

• 통합자연과학논문집
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• 제14권3호
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• pp.116-122
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• 2021

Properties and comparison of multivariate CUSUM and EWMA charts for monitoring Σ of multivariate normal N(${\underline{\mu}}$, Σ) process has considered. Comparison of the performances of the considered charts, the numerical values are obtained by simulation with 10,000 iteration in terms of ATS, ANSS and ANSW. We found that EWMA chart with small values of smoothing constant more effectively detects the process changes than with large smoothing constant. And we also found that CUSUM chart with small value of reference value is more effectively detecting the process change than with large reference value. If a process engineer has interest in detecting small amount of shift rather than large shift, he/she can be recommended to use small smoothing constant in EWMA chart and small reference value in CUSUM chart.

• Communications for Statistical Applications and Methods
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• 제30권3호
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• pp.227-244
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• 2023

In this paper, a depth-based nonparametric test for a multivariate two-sample scale problem is proposed. The proposed test statistic is based on the depth-induced ranks and is thus distribution-free. In this article, the depth values of data points of one sample are calculated with respect to the other sample or distribution and vice versa. A comprehensive simulation study is used to examine the performance of the proposed test for symmetric as well as skewed distributions. Comparison of the proposed test with the existing depth-based nonparametric tests is accomplished through empirical powers over different depth functions. The simulation study admits that the proposed test outperforms existing nonparametric depth-based tests for symmetric and skewed distributions. Finally, an actual life data set is used to demonstrate the applicability of the proposed test.

• Environmental Engineering Research
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• 제11권2호
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• pp.63-76
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• 2006

Multivariate analysis and batch monitoring on a pilot-scale sequencing batch reactor (SBR) are described for integrated wastewater treatment management system, where a batchwise multiway independent component analysis method (MICA) are used to extract meaningful hidden information from non-Gaussian wastewater treatment data. Three-way batch data of SBR are unfolded batch-wisely, and then a non-Gaussian multivariate monitoring method is used to capture the non-Gaussian characteristics of normal batches in biological wastewater treatment plant. It is successfully applied to an 80L SBR for biological wastewater treatment, which is characterized by a variety of error sources with non-Gaussian characteristics. The batchwise multivariate monitoring results of a pilot-scale SBR for integrated wastewater treatment management system showed more powerful monitoring performance on a WWTP application than the conventional method since it can extract non-Gaussian source signals which are independent and cross-correlation of variables.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.119-130
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• 2017

다변량 분포에서의 VaR (Value at Risk)와 CTE (Conditional Tail Expectation)에 관한 많은 연구문헌에서는 특정한 포트폴리오 구성비를 이용하여 일변량 분포로 변환하여 추정하였다. 다변량 분포에서 분위수에 관한 많은 연구가 존재한다. 그러나 분위수가 유일하게 존재하지 않으므로, VaR와 CTE의 추정에 어려움이 있다. 본 연구에서는 다변량 분위 벡터를 이용한 대안적인 VaR와 통합적인 다변량 CTE의 연구를 확장하여, 여러 종류의 포트폴리오로 구성된 다양한 비율 조합에 따른 가중 CTE 벡터들을 제안한다. 일변량에 대한 CTE 관계식을 다차원의 관계식으로 확장하고, 일변량의 관계식과의 특징과 차이점에 대하여 토론한다. 정규분포로부터 추출한 자료와 실증 예제를 통하여 본 연구에서 제안한 가중 CTE를 탐색하면서 가중 CTE의 활용성과 장점을 유도한다.

• 응용통계연구
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• 제26권6호
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• pp.903-913
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• 2013

최근 소셜 네크워크 서비스의 발달로 인해 개인의 감정이나 의견을 표현하는 소셜 데이터들이 하루에도 수백만 건씩 생산되고 있다. 또한 소셜 데이터는 개인의 의견에 또 다른 생각을 더하는 등 정보의 생산과 소비가 누구나 가능해짐으로써 사회현상을 잘 반영해주는 도구로 성장하고 있다. 본 연구에서는 블로그에 올라온 부정적인 감성어들을 분석하여 블로거의 감성변화를 탐지하기 위해 다변량 관리도를 이용하고자 한다. 이를 위해 2008년 1월 1일부터 2009년 12월 31일 사이에 생성되었던 모든 블로그를 사용하였다. 품질 특성치가 다변량으로 주어지는 경우 호텔링의 $T^2$ 관리도가 널리 사용된다. 그러나 이 관리도는 품질 특성치들의 분포가 다변량 정규분포라는 가정을 하고 있어, 비정규 다변량 자료에 대한 관리도의 성능은 좋지 않다. 이에 본 논문에서는 Sun과 Tsung (2003)이 제안한 써포트 벡터머신에서 단일 집합 분류 기법 중 하나인 SVDD(support vector data description) 알고리즘과 이를 확장한 K-관리도를 소개하고, 실제 데이터 분석에 적용해 보았다.