• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.663-669
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• 2014

Background: With recent progress in health science administration, a huge amount of data has been collected from thousands of subjects. Statistical and computational techniques are very necessary to understand such data and to make valid scientific conclusions. The purpose of this paper was to develop a statistical probability model and to predict future survival times for male breast cancer patients who were diagnosed in the USA during 1973-2009. Materials and Methods: A random sample of 500 male patients was selected from the Surveillance Epidemiology and End Results (SEER) database. The survival times for the male patients were used to derive the statistical probability model. To measure the goodness of fit tests, the model building criterions: Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were employed. A novel Bayesian method was used to derive the posterior density function for the parameters and the predictive inference for future survival times from the exponentiated Weibull model, assuming that the observed breast cancer survival data follow such type of model. The Markov chain Monte Carlo method was used to determine the inference for the parameters. Results: The summary results of certain demographic and socio-economic variables are reported. It was found that the exponentiated Weibull model fits the male survival data. Statistical inferences of the posterior parameters are presented. Mean predictive survival times, 95% predictive intervals, predictive skewness and kurtosis were obtained. Conclusions: The findings will hopefully be useful in treatment planning, healthcare resource allocation, and may motivate future research on breast cancer related survival issues.

• Water for future
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• v.29 no.1
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• pp.129-139
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• 1996

It is very important to select appropriate distributions for hydrological data in planning and designing hydraulic structures. Also, it is necessary to check whether the selected distribution reproduces the statistical characteristics of the real data. In this study, the parameters of the two- and three-parameter gamma, two- and three-parameter lognormal, Gumbel, two- and three-parameter log-Gumbel, GEV, log-Pearsonn type III, two- and three-parameter Weibull, four- and five-parameter Wakeby distributions were estimated for the rainfall data of 22 sites in Korea with 7 different durations based on the methods of moments, probability weighted moments, and maximum likelihood. And the validity conditions were checked for the estimated parameters. The separation effect for each distribution was examined throught 10,000 simulations using the estimated parameters. As results, the separation effect was the smallest: log-Pearson type III for moment method, log-Pearson type III and GEV for probability weighted moment method, and GEV for maximum likelihood method. However, it is large for the two-parameter distributions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.197-205
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• 2008

In order to estimate mean wind speed in the Gwangyang-Myodo Region, the probability distribution model of extreme values has been used in the statistical analysis of joint distribution probability of daily maximum wind speed and corresponding direction in this paper. For this purpose frequency of daily maximum records at respective stations is inquired into and sample of largest yearly wind speed of sixteen compass direction and non-direction is extracted from daily data of maximum wind speed and appropriate direction of the meteorological observing stations nearby the bridge construction site. These extreme speed records are applied to Gumbel and Weibull distribution model and parameters are estimated through method of moment and method of least squares etc. And also, distribution and parameters are inquired into whether it is fitted through the probability plot correlation coefficient examination. From fitted parameters the largest yearly wind speed of sixteen compass direction and non-direction is extrapolated taking into account factors regarding sample size of data and distance from the bridge construction site according to the appropriate stations.

• Proceedings of the KIEE Conference
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• 1998.07d
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• pp.1475-1477
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• 1998

In this paper, breakdown strength and time to breakdown are experimented under semiconducting layer/needle electrode in XLPE which is used for power cable insulator. Shape and scale parameters of obtained data are estimated using 2-parameters Weibull distribution. Life-time coefficient(n-value) using shape parameters for breakdown strength and time to breakdown tests is estimated. n-value of 1000 hour aged XLPE showed higher value than that of virgin XLPE. Increase of n-value is estimated by the stability due to removal of by-product and residue gas in XLPE by heating.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.199-207
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• 2001

The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.83-84
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• 2007

• International Journal of Reliability and Applications
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• v.9 no.2
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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.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.1003-1008
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• 2002

The purpose of this research was to obtain fatigue property of pavement concrete by split tension fatigue test. The specimens of pavement concrete were fabricated using the concrete at jop site. The fatigue tests of split tension were performed by 4 stress levels(90%, 80%, 70%, 60%) and 3 stress ratio(0.1, 0.3, 0.5). From this research, the S-N relationship, S-N-P relationship was derived and Weibull probability density functions was plotted using the distribution parameters.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1995.11a
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• pp.310-312
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• 1995

In order to evaluate insulating reliability in epoxy composites, breakdown data were experimented in the temperature range of 20[$^{\circ}C$]∼160[$^{\circ}C$]. From these data, various parameters which are used in Weibull distribution could be derived, and using them, the reliability on a breakdown probability was calculated.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.150-155
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• 2002

En case of the fatigue life evaluation of rolling stock structures, mainly deterministic fatigue life evaluation has been carried out. But most of the parameters influencing on the fatigue life have a probabilistic distribution such as normal, log-normal, Weibull, etc. Therefore, to take probabilistic factors into fatigue life evaluation, probabilistic methods are being applied to the fatigue life evaluation of rolling stock. In this paper, probabilistic S-N analysis and methods using limit state functions are introduced. And some results of fatigue life evaluation obtained with these methods for rolling stock structures are shown.