• Journal of Integrative Natural Science
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• v.4 no.2
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• pp.121-129
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• 2011

The purpose of this paper is to estimate the fluctuation of an earning rate and risk management using the price index of Korea stocks. After an observation of conception of fluctuation, we can show volatility clustering and fluctuation phenomenon in the Korea stock price index using GARCH model with heteroscedasticity. In addition, the effects of fluctuation on the time-series was evaluated, which showed the heteroscedasticity. MCMC method and Winbugs as Bayesian computation were used for analysis.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1331-1336
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• 2008

This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1144-1150
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• 2009

This paper investigates the feasibility of the Bayesian discrete time approximation method to estimate the parameters of Weibull distributions of failures for two non-identical components connected in series system. A Bayesian model based on the discrete time approximation method is formulated to infer the Weibull parameters of two non-identical components with the failure data of the virtual tests. The study of this paper comes to a conclusion that the method is feasible only for some special cases under the given constraints on the concerned parameters.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5225-5231
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• 2015

Background: One of the most prevalent cancers in whole world is skin cancer and its prevalence is growing. The present research sought to estimate relative risk of morbidity and mortality due to skin cancer. Materials and Methods: In this cross-sectional study. The required data were gathered from the registered cancer reports of Cancer Control Office in the Center for Non Communicable Disease of the Iranian Ministry of Health (MOH). The data were extracted at province level in the time span of 2008-10. WINBUGS software was used to analyze the data and to identify high risk regions. ArcGIS10 was utilized to map the distribution of skin cancer and to demonstrate high risk provinces by using classic and fully Bayesian models taking into account spatial correlations of adjacent regions separately for men and women. Results: Relative risk of morbidity for women in Yazd and for men in Kurdistan and relative risk of mortality for women in Bushehr and for men in Kohgiluyeh were found to be the highest. Bayesian model due to regarding adjacent regions correlation, have precise estimation in comparing to classical model. More frequent epidemiological studies to enact skin cancer prevention programs. Conclusions: High risk regions in Iran include central and highland regions. Therefore it is suggested that health decision makers enact public education, using anti UV creams and sunglasses for those parts as a short preventing program.