• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• 물과 미래
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• 제23권1호
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• pp.99-107
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• 1990

수자원 개발계획 및 목공구조물의 합리적 설계를 위해서는 과거의 수문관측자료에 의거한 해석이 필요하며, 일반적인 수문현상은 무작위적인 인자가 포함되기 때문에 이를 고려한 통계적 기법, 즉 추계학적 해석기법이 필요하다고 하겠다. 본 연구에서는 남한강 상류의 동일유역 4개 지점(단양, 정선, 영월, 평창)의 월유량 자료를 일변량 AR(1), AR(2)모형과 다변량 AR(1), AR(2)모형에 적용하여 각 모형의 통계적 특성치를 분석하고, 월유량을 모의발생시켜, 일변량 모형과 다변량 모형을 비교하였다. 각각의 모형에 의한 모의발생 계열의 비교, 분석을 통하여 볼 때, 단일지점만을 고려하는 일변량 모형에 비해 지점간의 공선형성을 고려하는 다변량 모형이 동일유역의 월유량 해석에 있어서 더 적합함을 알 수 있었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.166-166
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• 2023

Compound hazards (CHs) are two or more extreme climate events combined which occur simultaneously in the same region at the same time. Compared to individual hazards, the combination of hazards that cause CHs can result in greater economic losses and deaths. While several extreme climate events have been recorded across Asia for the past decades, many studies have only focused on a single hazard. In this study, we assess the spatiotemporal pattern of dry compound hazards which includes drought, heatwave, fire and wind across Asia for the last 42 years (1980-2021) using the historical data from ERA5 Reanalysis dataset. We utilize a daily spatial data of each climate event to assess the occurrence of such compound hazards on a daily basis. Heatwave, fire and wind hazard occurrences are analyzed using daily percentile-based thresholds while a pre-defined threshold for SPI is applied for drought occurrence. Then, the occurrence of each type of compound hazard is taken from overlapping the map of daily occurrences of a single hazard. Lastly, a multivariate assessment are conducted to quantify the occurrence frequency, hotspots and trends of each type of compound hazard across Asia. By conducting a multivariate analysis of the occurrence of these compound hazards, we identify the relationships and interactions in dry compound hazards including droughts, heatwaves, fires, and winds, ultimately leading to better-informed decisions and strategies in the natural risk management.

• Communications for Statistical Applications and Methods
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• 제7권2호
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• pp.385-392
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• 2000

Many tests for multivariate normality are based on the spherical coordinates of the scaled residuals of multivariate observations. Moore and Stubblebine's (1981) Pearson chi-square test is based on the radii of the scaled residuals, or equivalently the sample Mahalanobis distances of the observations from the sample mean vector. The chi-square statistic does not have a limiting chi-square distribution since the unknown parameters are estimated from ungrouped data. We will derive a simple closed form of the Rao-Robson chi-square test statistic and provide a self-contained proof that it has a limiting chi-square distribution. We then provide an illustrative example of application to a real data with a simulation study to show the accuracy in finite sample of the limiting distribution.

• 대한인간공학회지
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• 제24권4호
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• pp.39-46
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• 2005

The purpose of the study is to suggest a methodology for properly categorizing the body type of Koreans based on the multivariate statistical analysis. Anthropometric data used in the study were measured from the sampled strata of about fifteen thousand Koreans surveyed through the 5th national anthropometic data measurement project called Size Korea funded by ATS, Korea, during 2003-2004. In order to categorize whole body types, the normalized anthropometric variables, being divided by its stature, were used for obtaining a set of factors that supposedly represent body types through the factor analysis. These factors, which were again clustered, yielded the body types according to the gender. The body types classified are expected to be applied to product design for clothing, furniture, automobile packaging, etc.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 가을 학술발표회 논문집
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• pp.493-500
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• 2000

Rock Mass Rating has been widely applied to the underground tunnel excavation and many other practical problems in rock engineering. However, Rock Mass Rating is hard to make out because it is difficult to estimate each valuation items through all kind of field situations and items of RMR have interdependence. So the experts of tunnel assessment have problems with rating rock mass. In this study, using multivariate analysis based on domestic data(1011EA) of water conveyance tunnel, we presented rock mass rating system which is objective and easy to use. The constituents of RMR are decided to RQD, condition of discontinuities, groundwater conditions, orientation of discontinuities, intact rock strength, spacing of discontinuities in important order. In each step, we proposed the best multiple regression model for RMR system. And using data which have been collected at other site, we examined that presented multiple regression model was useful.

• 품질경영학회지
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• 제34권4호
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• pp.102-109
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• 2006

This paper investigates the effects of non-normality on the performance of univariate and multivariate cumulative sum(CUSUM) control charts for monitoring the process mean. In-control and out-of-control average run lengths of the charts are examined for the univariate/multivariate lognormal and t distributions. The effects of the reference value and the correlation coefficient under the non-normal distributions are also studied. Simulation results show that the CUSUM charts with small reference values are robust to non-normality but those with moderate or large reference values are sensitive to non-normal data especially to process data from skewed distributions. The performance of the chart to detect mean shift of a process is not invariant to the direction of the shift for skewed distributions.

• 품질경영학회지
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• 제19권2호
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• pp.63-77
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• 1991

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the inspection method and technical innovation constraining the motor vehicle emission. In order to establish the more reasonable certified test, the multivariate sequential rectifying inspection plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This inspection method is designed to satisfy the evaluation measure constraining domestic vehicle emission, and it serves the defect rectifying system and performance certification of catalytic converts. As the prior parameter for the domestic vehicles, we used the data for the catalytic converts which passed the certified test excuted by the EPK. For the case of engine test, we used those data which passed the certified test of domestic vehicles. The multivariate sequential rectifying inspection plan of the vector parameter is able to minimize the average sample number and increase the pass probability of operating characteristic curve.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.525-533
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• 2015

Modern production process is a very complex structure combined observations which are correlated with several factors. When the error signal occurs in the process, it is very difficult to know the root causes of an out-of-control signal because of insufficient information. However, if we know the time of the change, the system can be controlled more easily. To know it, we derive a maximum likelihood estimator (MLE) of the change point in a process when observations are from a multivariate IMA(1,1) process by monitoring residual vectors of the model. In this paper, numerical results show that the MLE of change point is effective in detecting changes in a process.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.79-89
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• 1999

중복수가 있는 조사는 추출단위 (병원, 가구)가 단순임의추출 또는 층화임의추출을 통해 추출되고 추출단위들이 여러 조사단위 (환자, 사람)들과 서로 연결되어 있는 경우를 말한다. 연결형태에 따른 조사단위의 집합을 network라 정의하면 network는 하나 이상의 추출단위와 연결될 것이고 하나의 추출단위는 하나이상의 network와 연결이 될 것이다. 본 논문에서는 두 개 이상의 변수가 연결되는 중복수가 있는 다변량 층화임의추출의 경우에 배분문제를 연구하였다.