• 응용통계연구
• /
• 제21권1호
• /
• pp.19-33
• /
• 2008

연속 형질(quantitative trait)에 영향을 미치는 유전자를 알아내기 위해 형제 쌍의 자료를 수집하여, 주로 이용되는 Haseman과 Elston (1972)의 최소제곱 회귀검정법으로 분석하는데 이는 단일 형질에 대한 분석법이다. 현실적으로 여러 형질들이 복잡하게 단일유전자 좌위(single locus)와 연관되어 있어 함께 수집하게 되는 경우에는, 이러한 연관된 여러 형질을 동시에 분석하는 유전연관성 검정법(linkage test)이 절실히 필요한 실정이다. Amos 등 (1990)은 주성분(principal component) 선형모형을 이용하여 Haseman과 Elston (1972)방법을 둘 이상의 형질의 다변량 분석법으로 확장시켰다. 그러나 이 검정방법은 통계량의 분포를 알 수 없기에 아직 제 1종 오류가 제대로 통제되지 못하는 문제를 가지고 있다. 본 논문에서는 이러한 다변량 형질 자료의 연관성검정에 있어 단일변량에 대한 비모수 추세검정법을 다변량 자료에 대한 분석법으로 확장시킨 통계량을 사용할 것을 제안한다. Amos 등 (1990)이 제안한 방법과 다변량 추세검정 통계량을 모의실험으로 생성한 연속형 형질자료에 적용하였을 때, 다변량 추세검정 통계량은 Amos 등 (1990) 방법에서의 여러 문제점이 발생되지 않을 뿐만 아니라 모의실험에서 제 1종 오류가 정해진 유의수준에 가까운 것을 확인하였고, 검정적이 더 높음을 볼 수 있었다.

• 대한인간공학회지
• /
• 제12권2호
• /
• pp.63-83
• /
• 1993

The primary objective of the research is to develop a mathematical method to incorporate the variability of anthropometric body dimensions and joint strengths of individuals in a biomechanical analysis. A multivariate normal simulation model estimated anthropometric body dimensions and joint strengths of the random link-person, based on the assumptions that the vari- ables of body dimensions and joint strengths are correlated and follow normal distributions. Statistical comparative analysis demonstrated that the random link-person represented a more realistic human-like form in an anthropometric sense than the proportional link-person whose body dimensions were estimated proportionally. Estimated joint strengths for the random link-person, however, did not match the measured joint strengths as closely as the estimated body dimensions. The random link-person will allow biomechanical analysis of manual materials handling tasks to be individualized with respect to the anthropometry and a static strength.

• 통합자연과학논문집
• /
• 제15권1호
• /
• pp.1-8
• /
• 2022

In a multivariate normal production process N_p(µ,Σ), a chart combining three EWMA charts with accumulate-combine method for µ, variance components of Σ, and off-diagonal elements of Σ, into a EWMA (exponentially weighted moving average) chart is considered, which is called a combined EWMA chart. Through simulation work, the proposed combined EWMA chart's numerical performance and properties are examined. The simulation results show that the proposed combined EWMA chart, which is simultaneously monitoring all the process parameters of multivariate normal production process, works effectively in the perspective of means, variances and correlation coefficients. In addition, the combined EWMA chart is extended to VSI chart.

• 한국통계학회:학술대회논문집
• /
• 한국통계학회 2000년도 추계학술발표회 논문집
• /
• pp.147-152
• /
• 2000

A Bayesian criterion is proposed for a multiple test of two independent multivariate normal populations. For a Bayesian test the fractional Bayes facto.(FBF) of O'Hagan(1995) is used under the assumption of Jeffreys priors, noninformative improper proirs. In this test the FBF without the need of sampling minimal training samples is much simpler to use than the intrinsic Bayes facotr(IBF) of Berger and Pericchi(1996). Finally, a simulation study is performed to show the behaviors of the FBF.

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

• 대한산업공학회지
• /
• 제27권3호
• /
• pp.289-296
• /
• 2001

This paper proposes multivariate control chart for autocorrelated data which are common in chemical and process industries and lead to increase in the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a vector autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and therefore the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and Monte Carlo simulation is conducted to investigate the performances of the proposed control charts.

• 품질경영학회지
• /
• 제40권3호
• /
• pp.337-346
• /
• 2012

Purpose: A Control chart is one of the important statistical process control tools that can improve processes by reducing variability and defects. Methods: In the present study, we propose the local $T^2$ multivariate control chart that can efficiently detect abnormal observations by considering the local pattern of the in-control observations. Results: A simulation study has been conducted to examine the property of the proposed control chart and compare it with existing multivariate control charts. Conclusion: The results demonstrate the usefulness and effectiveness of the proposed control chart.

• Communications for Statistical Applications and Methods
• /
• 제8권1호
• /
• pp.97-107
• /
• 2001

A simultaneous test criterion for multiple hypotheses concerning comparison of two multivariate normal populations is considered by using the so called Bayes factor method. Fully parametric frequentist approach for the test is not available and thus Bayesian criterion is pursued using a Bayes factor that eliminates its arbitrariness problem induced by improper priors. Specifically, the fractional Bayes factor (FBF) by O'Hagan (1995) is used to derive the criterion. Necessary theories involved in the derivation an computation of the criterion are provided. Finally, an illustrative simulation study is given to show the properties of the criterion.

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

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