• Communications for Statistical Applications and Methods
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• 제20권4호
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• pp.283-290
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• 2013

Subjects can experience two types of recurrent events in a longitudinal study. In addition, there may exist intermittent dropouts that results in repeated observation gaps during which no recurrent events are observed. Therefore, theses periods are regarded as non-risk status. In this paper, we consider a special case where information on the observation gap is incomplete, that is, the termination time of observation gap is not available while the starting time is known. For a statistical inference, incomplete termination time is incorporated in terms of interval-censored data and estimated with two approaches. A shared frailty effect is also employed for the association between two recurrent events. An EM algorithm is applied to recover unknown termination times as well as frailty effect. We apply the suggested method to young drivers' convictions data with several suspensions.

• 응용통계연구
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• 제25권4호
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• pp.621-632
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• 2012

Recurrent event data can be easily found in longitudinal studies such as clinical trials, reliability fields, and the social sciences; however, there are a few observations that disappear temporarily in sight during the follow-up and then suddenly reappear without notice like the Young Traffic Offenders Program(YTOP) data collected by Farmer et al. (2000). In this article we focused on inference for a cumulative mean function of the recurrent event data with these incomplete observation gaps. Defining a corresponding risk set would be easily accomplished if we know the exact intervals where the observation gaps occur. However, when they are incomplete (if their starting times are known but their terminating times are unknown) we need to estimate a distribution function for the terminating times of the observation gaps. To accomplish this, we treated them as interval-censored and then estimated their distribution using the EM algorithm proposed by Turnbull (1976). We proposed a nonparametric estimator for the cumulative mean function and also a nonparametric test to compare the cumulative mean functions of two groups. Through simulation we investigated the finite-sample performance of the proposed estimator and proposed test. Finally, we applied the proposed methods to YTOP data.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1117-1125
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• 2014

In a longitudinal study, subjects can experience same type of events repeatedly. Also, there may exist intermittent dropouts resulting in repeated observation gaps during which no recurrent events are observed. Furthermore, when such observation gaps have incomplete forms caused by the unknown termination times of observation gaps, ordinary approaches result in biased estimates. In this study, we investigate the effect of ignoring observation gaps and propose methods to overcome this problem. For estimating the distribution of unknown termination times, an interval-censored mechanism is applied and two cases are considered. Simulation studies are carried out to evaluate the performance of the proposed method. Conviction data of young drivers with several suspensions are analyzed to illustrate the suggested approach.

• Journal of the Korean Data and Information Science Society
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• 제13권1호
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• pp.139-145
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• 2002

This paper deals with the problem of obtaining the Bayesian predictive density function and the prediction intervals for a future observation and the p-th order statistics of n future observations for the exponential model under the censored sampling with incomplete information.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.49-63
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• 1997

We consider the problem of classifying a p x 1 observation into one of two multivariate normal populations when the training smaples contain a block of missing observation. A new classification procedure is proposed which is a linear combination of two discriminant functions, one based on the complete samples and the other on the incomplete samples. The new discriminant function is easy to use.

• Journal of the Korean Data and Information Science Society
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• 제25권2호
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• pp.327-336
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• 2014

재발 사건 자료란 연구대상이 같은 종류의 사건을 반복적으로 경험할 때 발생하는 자료이다. 이러한 재발 사건은 사회과학, 자연과학, 공학, 의약학 등 다양한 분야에서 나타날 수 있다. 재발 사건자료를 분석할 때 연구자의 관심에 따라 사건 발생시간이나 사건 발생간의 소요시간을 이용하여 분석할 수 있다. 이 논문에서는 사건 발생시점간의 소요시간을 이용하여 불완전한 관측을 가진 재발 사건자료를 분석하고자 한다. 이 자료의 특징은 일부 관측대상들이 일정기간 동안 연구에서 제외되는 관측틈을 갖는다는 것이다. 이 때 관측틈은 불완전한 형태로 나타나게 되는데 그 이유는 관측틈의 시작시점은 알고 있지만 종료시점은 알 수 없기 때문이다. 이러한 미지의 종료시점을 추정하기 위해서 구간 중도 절단 방법이 적용된다. 따라서 종료시점이 추정된 후 프레일티를 포함한 회귀모형을 적용하여 공변량이 사건 재발에 미치는 영향을 알아볼 수 있다. 또한 제안한 방법을 실제자료에 적용하여 관측틈을 고려한 경우와 고려하지 않은 경우를 비교하고자 한다.

• 대한임베디드공학회논문지
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• 제3권2호
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• pp.109-118
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• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

• Journal of the Korean Statistical Society
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• 제18권1호
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• pp.13-25
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• 1989

This paper suggests a classification rule with unequal covariance matrices when a patterned incomplete data are involved in the discriminant analysis. This is an extension of Geisser's (1966) result to the case of missing observations. For the calssificaiton rule, we introduce an algorithm which contains data augmentation step and Monte Carlo integration step and show that the algorithm yields a consistant estimator of true classification probability. The proposed method is compared to the complete observation vector method through a Monte Carlo study. The results show that the suggested method, in general, performs better than the complete observation vector method which ignores those vectors of observation with one or more missing values from the analysis. The results also verify the consistency of the algorithm.

• 한국정보과학회논문지:데이타베이스
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• 제37권3호
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• pp.171-175
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• 2010

본 논문에서는 RFID 전자태그에 부착된 메모리의 정보를 접근할 때 발생하는 태그 연산 실행의 불완전성에 따른 태그 데이터의 불일치 문제를 분석하고, 이를 해결하기 위한 프로토콜을 제안한다. 수동형 RFID 태그는 통신의 불확실성과 단절성으로 인해 태그 메모리 접근연산의 완전한 실행을 보장하지 못하므로, 불완전하게 실행된 연산으로 인해 태그 데이터의 비일관성을 초래하는 문제가 발생한다. 본 논문에서는 태그 접근의 일관성을 유지하면서 불완전 연산의 실행을 완료시키기 위한 동시성 제어 프로토콜을 제안한다. 이 프로토콜은 불완전 실행된 연산의 대상태그를 연속질의로 정의하고 태그의 인식을 모니터링 함으로써 다른 연산들에 의한 불확실 데이타의 접근을 차단하고, 재수행을 통해 불완전하게 실행된 연산의 수행을 완료시킨다. 또한, 증명을 통해 제안한 프로토콜의 정확성, 일관성을 입증하였으며, 실험을 통해 본 프로토콜이 기존의 일관성 유지기법보다 좋은 성능을 나타냄을 보였다.

• 한국학교ㆍ지역보건교육학회지
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• 제19권1호
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• pp.71-83
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• 2018

Background & objectives: This study was aimed to identify the hand hygiene (HH) compliance and related factors among teachers working at child day care centers. Method: This study was done with 44 teachers working at home child day care center in Changwon. Data on hand hygiene compliance was measured using direct observation method from July to December, 2016 with structured observation sheet. Collected data was analyzed by descriptive statistics, and t-test or ANOVA using SPSS Statistics version 23.0. Result: Complete HH compliance rate was 54.0%, the highest in 'before having meals' (81.6%) and the lowest in 'after having meals' (25.8%). However, incomplete HH compliance rate was 34.5%, the highest in 'after contact with secretions' (47.8%) and the lowest in 'before having meals' (18.4%). The HH rate was related with working experience. Conclusion: The HH compliance rate among child care teachers was not satisfactory. About one quarter of child care teachers have taken hand hygiene related training. Therefore, child care teachers should be encouraged to participate in hand hygiene related education program regularly.