• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.327-336
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• 2000

We are mainly interested in hazard rate changes which are usually occur in survival times of manufactured products or patients. We may expect early failures with one hazard rate and next another hazard rate. For this type of data we apply a hazard rate change-point model and estimate the unkown time point to improve the model adequacy. We introduce change-point logistic model to the discrete time hazard rates. The MLEs are obtained routinely and we also explain the suggested model through a dataset of survival times.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.753-763
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• 2002

When there is one change-point in the hazard rate model, a change-point estimator with the partial score process is suggested and compared with the previously developed estimators. The limiting distribution of the partial score process we used is a function of the Brownian bridge. Simulation study gives the comparison of change-point estimators.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.359-370
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• 1999

We considered a change-point hazard rate model generalizing constant hazard rate model. This type of model is very popular in the sense that the Weibull and exponential distributions formulating survival time data are the special cases of it. Maximum likelihood estimation and the asymptotic properties such as the consistency and its limiting distribution of the change-point estimator were discussed. A parametric bootstrap method for finding confidence intervals of the unknown change-point was also suggested and the proposed method is explained through a practical example.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1225-1238
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• 2015

In this research, we fit various survival models and conduct tests and estimation for the hazard change-point with the rectal cancer data. By the log-rank tests, at significance level ${\alpha}=0.10$, survival functions are significantly different according to the uniporter of glucose (GLUT1), clinical stage (cstage) and pathologic stage (ypstage). From the Cox proportional hazard model, the most significant covariates are GLUT1 and ypstage. Assuming that the rectal cancer data follows the exponential distribution, we estimate one hazard change-point using Matthews and Farewell (1982), Henderson (1990) and Loader (1991) methods.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1253-1262
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• 2016

When there exists a change-point in hazard function, it should be estimated for exact parameter or hazard estimation. In this research, we compare the hazard change-point estimators. Matthews and Farewell (1982) parametric change-point estimator is based on the likelihood and Zhang et al. (2014) nonparametric estimator is based on the Nelson-Aalen cumulative hazard estimator. Simulation study is done for the data from exponential distribution with one hazard change-point. The simulated data generated without censoring and the data with right censoring are considered. As real data applications, the change-point estimates are computed for leukemia data and primary biliary cirrhosis data.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.163-175
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• 1998

The change of hazard rates at some unknown time point has been the interest of many statisticians. But it was restricted to the constant hazard rates which correspond to the exponential distribution. In this paper we generalize the change-point model in which any specific functional forms of hazard rates are net assumed. The assumed model includes various types of changes before and after the unknown time point. The Nelson estimator of cumulative hazard function is introduced. We estimate the change-point maximizing slope changes of Nelson estimator. Consistency and asymptotic distribution of bootstrap estimator are obtained using the martingale theory. Through a Monte Carlo study we check the performance of the proposed method. We also explain the proposed method using the Stanford Heart Transplant Data set.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.1
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• pp.12-22
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• 2016

Lidar-based hazard avoidance landing system for lunar lander calculates hazard cost with respect to the desired local landing area in order to identify hazard and designate safe landing point where the cost is minimum basically using slope and roughness of the landing area. In this case, if the parameters are only considered, chosen landing target can be designated near hazard threatening the lander. In order to solve this problem and select optimal safe landing point, hazard cost based on relative distance to hazard should not be considered as well as cost based on terrain parameters. In this paper, the effect of hazard cost based on relative distance to hazard on safe landing performance was analyzed and it was confirmed that landing site designation with two relative distances to hazard results in the best safe landing performance by an experiment using three-dimensional depth camera.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.801-812
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• 1999

Change-point hazard rate models arise for example in applying "burn-in" techniques to screen defective items and in studing times until undesirable side effects occur in clinical trials. Sometimes in screening defectives it might be sensible to model two stages of burn-in. In a clinical trial there might be an initial hazard rate for a side effect which after a period of time changes to an intermediate hazard rate before settling into a long term hazard rate. In this paper we consider the multiple change points hazard rate model. The classical approach's asymptotics can be poor for the small to all moderate sample sizes often encountered in practice. We propose a Bayesian approach avoiding asymptotics to provide more reliable inference conditional only upon the data actually observed. The Bayesian models can be fitted using simulation methods. Model comparison is made using recently developed Bayesian model selection criteria. The above methodology is applied to a generated data and to a generated data and the Lawless(1982) failure times of electrical insulation.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1048-1052
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• 2005

In Korean cases, the occupation of building construction is below 10% of the total industry workers but from a accident rate point of view, it is a risk serious industry and it's hazard is very considerable which accident rate is up to 30% of the total industry workers. The reason of high accident rate of the building construction is its own characteristic, hazard of the work in which is implicated and the shortage of safety counter plan and information, so it is most required to the building construction that educating, training, short and long period approaching to prevent the hazard. The safety information of building construction which is related to safety accident is divided into human and material such as hazard, work situation, cause and counter plan. The existing hazard cases imply all of the information about the work type and work progress of the building construction, so if the research of the every fact is well accomplished, we can obtain the useful information and prevent the hazard of building construction. From this point of view, the emphasis of this study is based on analyzing the cause of hazard first, suggesting the safety information each part of work type and work progress second, and finally making the all existing hazard cases to the Data Base and developing the safety information system.

• Magazine of the Korean Society of Hazard Mitigation
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• v.9 no.2
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• pp.52-60
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• 2009