• International Journal of Reliability and Applications
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• 제9권2호
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• pp.167-182
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• 2008

The objective of this paper is to discuss the stochastic analysis and the statistical inference of a three-states semi-Markov reliability model. Using the maximum likelihood procedure, the parameters included in this model are estimated. Based on the assumption that the lifetime and repair time of the system are gener-alized Weibull random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is derived. Many important special cases are discussed. Finally, the obtained results are compared with those available in the literature.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1053-1065
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• 2006

This paper proposes a method in one-way layouts for longitudinal data with informative drop-out. When dropouts are informative, that is, correlated with unobserved data and/or the previous observed data, the simple imputation methods such as 'last observation carried forward' (LOCF) methods would arise the bias of the testing models. The maximum likelihood procedure combined with a logit model for the drop-out process is proposed to test treatment effects for one factorial designs and compared with LOCF method in two examples.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.699-709
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• 2000

The constrained maximum likelihood estimation of the number of trials in several binomial populations under order restriction, such as simple order, is discussed. The estimation procedure is based on, so called, pool adjacent violators algorithm. Three handy estimators are given and their performances are compared using an artificial example.

• International Journal of Reliability and Applications
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• 제8권1호
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• pp.17-25
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• 2007

Maximum likelihood method is utilized to estimate the two parameters of generalized exponential distribution based on grouped and censored data. This method does not give closed form for the estimates, thus numerical procedure is used. Reliability measures for the generalized exponential distribution are calculated. Testing the goodness of fit for the exponential distribution against the generalized exponential distribution is discussed. Relevant reliability measures of the generalized exponential distributions are also evaluated. A set of real data is employed to illustrate the results given in this paper.

• Journal of applied mathematics & informatics
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• 제40권1_2호
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• pp.1-13
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• 2022

This article introduces a new distribution called length-biased powered inverse Rayleigh distribution. Some of its statistical properties are derived. Maximum likelihood procedure is applied to report the point and interval estimations of all model parameters. The proposed distribution is also applied to two real data sets for illustrative purposes.

• 한국지반공학회지:지반
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• 제14권3호
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• pp.95-108
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• 1998

지반의 S파 및 P파의 깊이에 따른 변화를 원위치에서 측정하기 위하여 다운흘 시험 (downhole testing)과 SCPT (seismic CPT) 등이 널리 사용되어 왔다. 다운홀 시험과 SCPT는 경제성, 운용의 용이성, 발진원의 단순성 등의 측면에서 효율적이기 때문에, 현재 지반조사에서 그 사용빈도가 더욱 증가하고 있는 추세이다. 특히 최근에는 다운흘과 SCPT의 자료 분석을 자동화하기 위한 노력의 일환으로 interval measurements의 기법이 활용되고 있는데, 현재 이에 대한 적절한 역산해석 (inversion analysis) 기법이 없는 형편이다. 따라서, 본 논문에서는 다운홀이나 SCPT의 interval measurements를 분석하기 위한 새로운 역산해석 기법을 제안하였다. 제안된 역산해석 기법의 정모델링(forward modeling)에서는 탄성파의 전파를 Snell의 법칙에 의거하여 굴절.반사되는 현상을 고려하였곡, 역산해석을 위해서는 최대공산법 (maximum likelihood method)을 적용하였다. 그리고, 본 논문에서 제안한 역산해석 기법의 검증을 위하여, 하나의 S파 주상도를 가정하고 이에 대하여 다운흘 시험을 모사하였다. 이론적으로 수행한 다운홀 시험 결과에 대하여 기존의 비 역산해석 방법과 본 논문에서 제안한 역산해 석 기법에 의해서 S파 주상도를 추정하였는데, 그 결과 본 논문에서 제시한 역산기법이 가장 정확한 결과를 도출하였으며, 다운홀 시험과 SCPT을 자동화하는데 효율적으로 적용이 될 수 있음을 입증하였다.

• ETRI Journal
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• 제34권5호
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.633-641
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• 2014

The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1581-1589
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• 2014

In this paper, we consider maximum likelihood estimators of the location and scale parameters for the half-logistic distribution when samples are multiply Type I hybrid censored. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($\hat{\sigma}_I$, $\hat{\sigma}_{II}$). We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The approximate MLE of the second type is better than that of the first type in the sense of the RMSE. Further an illustrative example with the real data is presented.

• International Journal of Reliability and Applications
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• 제6권2호
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• pp.65-78
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• 2005

In this paper we derive estimations of the parameters included in the distribution of the lifetime of k-out-of-m cold standby system with imperfect switches. Maximum likelihood and Bayes procedures are followed to get such estimations. Numerical studies, using Monte Carlo simulation method, are given in order to explain how we can utilize the theoretical results derived, and to compare the performance of the two different methods used. The criterion of comparisons is the mean squared errors associated with each estimate.