Bivariate EWMA Control Charts for Autocorrelated Processes

조교영,안영선,Cho, Gyo-Young,Ahn, Young-Sun The Korean Data and Information Science Society 2002 한국데이터정보과학회지 Vol.13 No.1

In this paper we establish bivariate exponentially weighted moving average (EWMA) control charts for autocorrelated processes using residual vectors. We first derive the residual vectors, their expectation, variance-covariance matrix, then evaluate the control chart based on the average run length (ARL).

Quadratic inference functions in marginal models for longitudinal data with time-varying stochastic covariates

조교영,Oyunchimeg Dashnyam 한국데이터정보과학회 2013 한국데이터정보과학회지 Vol.24 No.3

For the marginal model and generalized estimating equations (GEE) method there is important full covariates conditional mean (FCCM) assumption which is pointed out by Pepe and Anderson (1994). With longitudinal data with time-varying stochastic covariates, this assumption may not necessarily hold. If this assumption is violated, the biased estimates of regression coefficients may result. But if a diagonal working corre-lation matrix is used, irrespective of whether the assumption is violated, the resulting estimates are (nearly) unbiased (Pan et al., 2000).The quadratic inference functions (QIF) method proposed by Qu et al. (2000) is the method based on generalized method of moment (GMM) using GEE. The QIF yields a substantial improvement in efficiency for the estimator of beta when the working correlation is misspecified, and equal efficiency to the GEE when the working correlation is correct (Qu et al., 2000).In this paper, we interest in whether the QIF can improve the results of the GEE method in the case of FCCM is violated. We show that the QIF with exchangeable and AR(1) working correlation matrix cannot be consistent and asymptotically normal in this case. Also it may not be efficient than GEE with independence working correlation. Our simulation studies verify the result.

카즈분포족에 대한 누적합 관리도

조교영,Cho, Gyo-Young 한국데이터정보과학회 2011 한국데이터정보과학회지 Vol.22 No.1

결점수를 모니터링하기 위한 통계적 공정관리는 생산공정에 널리 사용된다. 결점 수를 모니터링 하는데는 c-관리도가 사용된다. 전통적인 c-관리도는 표본에서 결점의 발생은 포아송분포를 따른다는 가정 하에서 만들어진다. 포아송분포에 대한 가정이 맞지 않을 때에는 X-관리도가 사용될 수 있다. 누적합 관리도는 공정의 작은 변화를 찾는데 유용한 것으로 알려져 있다. 본 논문에서는 다양한 Katz 분포족으로부터 생성된 계수자료에 대하여 3시그마 X-관리도와 누적합 관리도의 효율을 평균런의길이에 근거하여 비교 한다. 즉, 자료가 어떤 분포로부터 생성되었는지 알 수 없을 때, X-관리도와 누적합 관리도를 비교하는 것이다. In statistical process control, the primary method used to monitor the number of nonconformities is the c-chart. The conventional c-chart is based on the assumption that the occurrence of nonconformities in samples is well modeled by a Poisson distribution. When the Poisson assumption is not met, the X-chart is often used as an alternative charting scheme in practice. And CUSUM-chart is used when it is desirable to detect out of control situations very quickly because of sensitive to a small or gradual drift in the process. In this paper, I compare CUSUM-chart to X-chart for the Katz family covering equi-, under-, and over-dispersed distributions relative to the Poisson distribution.

Upgraded quadratic inference functions for longitudinal data with type II time-dependent covariates

조교영,Oyunchimeg Dashnyam 한국데이터정보과학회 2014 한국데이터정보과학회지 Vol.25 No.1

Qu et. al. (2000) proposed the quadratic inference functions (QIF) method to marginal model analysis of longitudinal data to improve the generalized estimating equations (GEE). It yields a substantial improvement in efficiency for the estimators of regression parameters when the working correlation is misspecified. But for the longitudinal data with time-dependent covariates, when the implicit full covariates conditional mean (FCCM) assumption is violated, the QIF can not provide more consistent and efficient estimator than GEE (Cho and Dashnyam, 2013). Lai and Small (2007) divided time-dependent covariates into three types and proposed generalized method of moment(GMM) for longitudinal data with time-dependent covariates. They showed that their GMM type II and GMM moment selection methods can be more efficient than GEEwith independence working correlation (GEE-ind) in the case of type II time-dependent covariates. We develop upgraded QIF method for type II time-dependent covariates. We show that this upgraded QIF method can provide substantial gains in efficiency over QIF and GEE-ind in the case of type II time-dependent covariates.

Modified n-Level Skip-Lot Sampling Inspection Plans

조교영 한국데이터정보과학회 2008 한국데이터정보과학회지 Vol.19 No.3

This paper is the generalization of the modified two-level skip-lot sampling plan(MTSkSP2) to n-level. The general formulas of the operating characteristic(OC) function, average sample number(ASN) and average outgoing quality(AOQ) for the plan are derived using Markov chain properties.

Multivariate CUSUM Charts with Correlated Observations

조교영,안영선,Cho, Gyo-Young,Ahn, Young-Sun The Korean Data and Information Science Society 2001 한국데이터정보과학회지 Vol.12 No.1

In this article we establish multivariate cumulative sum (CUSUM) control charts based on residual vector with correlated observations. We first find the residual vector and its expectation and variance-covariance matrix and then evaluate the average run length (ARL) of the control charts.

Control Charts for Constant Failure Rate of System

조교영,이옥희,Cho, Gyo-Young,Lee, Ok-Hee 한국데이터정보과학회 2002 한국데이터정보과학회지 Vol.13 No.2

In this paper, we propose EWMA control charts using the life time data for the system with the constant failure rate, which were drawn from the fixed sampling interval without replacement(with replacement), and investigate the power of detection of EWMA by comparing ARL of EWMA control charts with one of Shewhart control charts.

다변량 통합공정관리의 재수정 절차에서 모수추정

조교영,박종숙 한국데이터정보과학회 2013 한국데이터정보과학회지 Vol.24 No.6

This paper considers the multivariate integrated process control procedure for detecting special causes in a multivariate IMA(1, 1) process. When the multivariate control chart signals, the special cause will be detected and eliminated from the process. However, when the elimination of the special cause costs high or is not practically possible, an alternative action is to readjust the process with approximately modified adjustment scheme. In this paper, we estimate parameters in the readjustment procedure after having a true signal in the multivariate integrated process control 다변량 통합공정관리의 기본절차는 잡음이 내재하는 공정에 수정조치를 취하여 공정편차벡터를백색잡음벡터로 전환하도록 하여 공정제곱편차벡터를 최소화하게 되는 것이며, 이러한 다변량 통합공정관리의 수정활동을 하는 경우 공정에 이상원인이 발생하면 관리도를 통해 이를 탐지하고 제거하게된다. 수정된 공정은 이상원인 발생 전에는 백색잡음이지만, 이상원인 발생 후 다양한 형태의 시계열모형으로 변환하게 된다. 만약 수정된 공정을 탐지하여 이상원인의 신호가 발생한 경우 교정활동을통하여 이를 제거해야 하지만, 구조적으로 교정이 불가능 하거나 교정활동의 비용이 많이 발생하는 경우에는 이상원인의 효과를 감안하여 수정활동을 재조정해야할 것이다. 이 논문에서는 공정모형으로다변량 IMA(1,1)모형을 가정하고 다변량 통합공정관리 절차를 수행하는 경우 이상신호가 발생한 후재수정 절차에서 필요한 모수추정을 하고자 한다.

Generalized methods of moments in marginal models for longitudinal data with time-dependent covariates

조교영,Oyunchimeg Dashnyam 한국데이터정보과학회 2013 한국데이터정보과학회지 Vol.24 No.4

The quadratic inference functions (QIF) method proposed by Qu et al. (2000) and the generalized method of moments (GMM) for marginal regression analysis of longitudinal data with time-dependent covariates proposed by Lai and Small (2007) both are the methods based on generalized method of moment (GMM) introduced by Hansen (1982) and both use generalized estimating equations (GEE). Lai and Small (2007)divided time-dependent covariates into three types such as: Type I, Type II and Type III. In this paper, we compared these methods in the case of Type II and Type III in which full covariates conditional mean assumption (FCCM) is violated and interested in whether they can improve the results of GEE with independence working correlation. We show that in the marginal regression model with Type II time-dependent covariates, GMM Type II of Lai and Small (2007) provides more efficient result than QIF and for the Type III time-dependent covariates, QIF with independence working correlation and GMM Type III methods provide the same results. Our simulation study showed the same results.

한국 근로자의 근로생애주기별 사고경험률

조교영,최은숙,권민정,이창훈 한국직업건강간호학회 2018 한국직업건강간호학회지 Vol.27 No.4