• 통합자연과학논문집
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• 제9권3호
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• pp.215-222
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• 2016

When the linear correlation of the quality variables are considerably high, multivariate control charts may be a more effective way than univariate charts which operate quality variables and process parameters individually. Performances and efficiencies of the multivariate control charts under multivariate normal process has been considered. Some numerical results are presented under small scale of the shifts in the process to see the improvement of the efficiency of EWMA chart and CUSUM chart, which use past quality information, comparing to Shewart chart, which do not use quality information. We can know that the decision of the optimum value of the smoothing constant in EWMA structure or the reference value in CUSUM structure are very important whether we adopt combine-accumulate technique or accumulate-combine technique under the given condition of process.

• 응용통계연구
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• 제17권1호
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• pp.35-47
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• 2004

본 논문에서는 Kim & Bickel(2003)에서 제안한 이변량 정규분포를 위한 검정통계량을 Fattorini(1986)의 방법을 이용하여 이변량 이상인 경우에도 실제적으로 사용가능 하도록 일반화하였다. Fattorini(1986)의 통계량은 Shapiro & Wilk(1965)의 일변량 정규분포를 위한 검정통계량을 다변량으로 확장한 것이다. 그리고 제안된 통계량은 Fat-torini(1986) 통계량의 근사통계량으로 생각할 수 있으며 표본의 크기가 클 때도 사용 가능하다. 또한 모의실험을 통하여 여러 가지 대립가설에서 기존의 통계량과의 검정력을 비교하였다.

• Industrial Engineering and Management Systems
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• 제11권4호
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• pp.385-389
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• 2012

With the development of computer storage and the rapidly growing ability to process large amounts of data, the multivariate control charts have received an increasing attention. The existing univariate and multivariate control charts are a single hypothesis testing approach to process mean or variance by using a single statistic plot. This paper proposes a multiple hypothesis approach to developing a new multivariate control scheme. Plotted Hotelling's $T^2$ statistics are used for computing the corresponding p-values and the procedure for controlling the false discovery rate in multiple hypothesis testing is applied to the proposed control scheme. Some numerical simulations were carried out to compare the performance of the proposed control scheme with the ordinary multivariate Shewhart chart in terms of the average run length. The results show that the proposed control scheme outperforms the existing multivariate Shewhart chart for all mean shifts.

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.236-241
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• 2022

We consider methods of estimating a binary regression function using a nonparametric kernel estimation when there is only one covariate. For this, the Nadaraya-Watson estimation method using single and double bandwidths are used. For choosing a proper smoothing amount, the cross-validation and plug-in methods are compared. In the real data analysis for case study, German credit data and heart disease data are used. We examine whether the nonparametric estimation for binary regression function is successful with the smoothing parameter using the above two approaches, and the performance is compared.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.423-435
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• 2023

The Jarque and Bera (1980) statistic is one of the well known statistics to test univariate normality. It is based on the sample skewness and kurtosis which are the sample standardized third and fourth moments. Desgagné and de Micheaux (2018) proposed an alternative form of the Jarque-Bera statistic based on the sample second power skewness and kurtosis. In this paper, we generalize the statistic to a multivariate version by considering some data driven directions. They are directions given by the normalized standardized scaled residuals. The statistic is a modified multivariate version of Kim (2021), where the statistic is generalized using an empirical standardization of the scaled residuals of data. A simulation study reveals that the proposed statistic shows better power when the dimension of data is big.

• Safety and Health at Work
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• 제8권2호
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• pp.162-168
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• 2017

Background: Pelvic ring fractures (PRFs) may influence the daily activities and quality of life of the injured. The aim of this retrospective study was to explore the functional outcomes and factors related to return to work (RTW) after PRF. Methods: During the years 2003-2012, 282 injured individuals aged 20-55 years on the date of the accident, were hospitalized and treated for PRFs in a large tertiary hospital in Athens, Greece. One hundred and three patients were traced and contacted; 77 who were on paid employment prior to the accident gave their informed consent to participate in the survey, which was conducted in early 2015 through telephone interviews. The questionnaire included variables related to injury, treatment and activities, and the Majeed pelvic score. Univariate and multiple regression analyses were used for statistical assessment. Results: Almost half of the injured (46.7%) fully RTW, and earning losses were reported to be 35% after PRF. The univariate analysis confirmed that RTW was significantly related to accident site (labor or not), the magnitude of the accident's force, concomitant injuries, duration of hospitalization, time to RTW, engagement to the same sport, Majeed score, and complications such as limp and pain as well as urologic and sexual complaints (p < 0.05 for all). On multiple logistic regression analysis, the accident sustained out of work (odds ratio: 6.472, 95% confidence interval: 1.626-25.769) and Majeed score (odds ratio: 3.749, 95% confidence interval: 2.092-6.720) were identified as independent predictive factors of full RTW. Conclusion: PRFs have severe socioeconomic consequences. Possible predictors of RTW should be taken into account for health management and policies.

• 패션비즈니스
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• 제15권6호
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• pp.176-203
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• 2011

In today's intensifying global competition, Korean fashion industry is relying on only qualitative data for feasibility study of future projects and developmental plan. This study was conducted in order to support establishment of a scientific and rational management system that reflects market demand. First, fashion market size was limited to the total amount of expenditure for fashion clothing products directly purchased by Koreans for wear during 6 months in spring and summer and 6 months in autumn and winter. Fashion market forecasting model was developed using statistical forecasting method proposed by previous research. Specifically, time series model was selected, which is a verified statistical forecasting method that can predict future demand when data from the past is available. The time series for empirical analysis was fashion market sizes for 8 segmented markets at 22 time points, obtained twice each year by the author from 1998 to 2008. Targets of the demand forecasting model were 21 research models: total of 7 markets (excluding outerwear market which is sensitive to seasonal index), including 6 segmented markets (men's formal wear, women's formal wear, casual wear, sportswear, underwear, and children's wear) and the total market, and these markets were divided in time into the first half, the second half, and the whole year. To develop demand forecasting model, time series of the 21 research targets were used to develop univariate time series models using 9 types of exponential smoothing methods. The forecasting models predicted the demands in most fashion markets to grow, but demand for women's formal wear market was forecasted to decrease. Decrease in demand for women's formal wear market has been pronounced since 2002 when casualization of fashion market intensified, and this trend was analyzed to continue affecting the demand in the future.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.1-10
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• 2015

본 연구에서는 한국프로야구 변천사를 야구 통계량들을 중심으로 살펴보았다. 분석방법으로는 1982년부터 2013년까지의 한국프로야구 데이터를 이용하여 야구 통계량들의 시계열 그래프와 상관계수를 이용하였다. 그 결과 유의수준 1%에서 연도와 유의한 양의 상관관계를 보인 통계량은 2루타, 타점, 4구, 삼진, 병살타, 사구, 출루율, OPS, 방어율, 폭투, WHIP이고, 유의한 음의 상관관계를 보인 통계량은 3루타, 도루자, 실책, 완투, 완봉, 보크였다. 상관계수가 유의한 야구통계량의 예측을 위해서는 Box-Jenkins의 ARIMA 모형을 이용하였다. 결론적으로 세월의 흐름과 가장 상관이 큰 것은 완투 횟수의 감소이며, 그 다음으로 삼진 개수의 증가를 들 수 있었다.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.277-286
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• 2012

신용평가모형에서 부도로 잘못 예측된 정상 차주의 비율과 정확하게 평가된 부도차주의 비율인 일변량 누적분포함수로 표현된 ROC 곡선을 이용하여 분류성과를 평가한다. 본 연구에서는 스코어 확률변수를 이변량으로 확장하여 부도와 정상 차주의 결합누적분포함수를 이용하여 표현할 수 있는 ROC 곡선을 제안한다. 이변량 평균벡터를 통과하는 확률변수의 선형 관계를 이용하여 이변량 ROC 곡선을 구현한다. 그리고 다양한 이변량 정규분포에 대한 ROC 곡선으로부터 분류성과를 탐색하고, 이에 대응하는 AUROC 통계량과 비교분석한다. 본 연구에서 제안한 이변량 ROC 곡선으로부터 분류기준에 적합한 최적분류점을 구하고 이를 통해 이변량 혼합분포함수의 최적 분류기준을 설정할 수 있음을 보인다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.161-161
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• 2023

Bias correction of values is a necessary step in downscaling coarse and systematically biased global climate models for use in local climate change impact studies. In addition to univariate bias correction methods, many multivariate methods which correct multiple variables jointly - each with their own mathematical designs - have been developed recently. While some literature have focused on the inter-comparison of these multivariate bias correction methods, none have focused extensively on the effect of diverse configurations (i.e., different combinations of input variables to be corrected) of climate variables, particularly high-dimensional ones, on the ability of the different methods to remove biases in uni- and multivariate statistics. This study evaluates the impact of three configurations (inter-variable, inter-spatial, and full dimensional dependence configurations) on four state-of-the-art multivariate bias correction methods in a national-scale domain over South Korea using a gridded approach. An inter-comparison framework evaluating the performance of the different combinations of configurations and bias correction methods in adjusting various climate variable statistics was created. Precipitation, maximum, and minimum temperatures were corrected across 306 high-resolution (0.2°) grid cells and were evaluated. Results show improvements in most methods in correcting various statistics when implementing high-dimensional configurations. However, some instabilities were observed, likely tied to the mathematical designs of the methods, informing that some multivariate bias correction methods are incompatible with high-dimensional configurations highlighting the potential for further improvements in the field, as well as the importance of proper selection of the correction method specific to the needs of the user.