• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.741-752
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• 2016

Numerous studies have shown that normal inverse Gaussian (NIG) distribution adequately fits the empirical return distribution of financial securities. The estimation of parameters can also be done relatively easily, which makes the NIG distribution more useful in financial markets. The maximum likelihood estimation and the method of moments estimation are easy to implement; however, we may encounter a problem in practice when a relationship among the moments is violated. In this paper, we investigate this problem in the parameter estimation and try to find a simple solution through simulations. We examine the effect of our adjusted estimation method with real data: daily log returns of KOSPI, S&P500, FTSE and HANG SENG. We also checked the performance of our method by computing the value at risk of daily log return data. The results show that our method improves the stability of parameter estimation, while it retains a comparable performance in goodness-of-fit.

• Food Science and Biotechnology
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• v.17 no.3
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• pp.659-663
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• 2008

Different statistical distribution functions were examined to find an adequate distribution function to describe the microbial contamination behavior of a Korean side dish product, seasoned soybean sprouts for different seasons and market groups. The triang distribution was the best for any market groups in winter, while the logistic distribution could describe the microbial contamination in log CFU/g for all the market groups in spring and summer. From parametric bootstrapping based on the fitted distributions, it was found that a normal distribution could describe the distribution of mean microbial count in log CFU/g for all the seasons and market groups. Statistical parameters for each season/market group are presented to estimate the confidence interval.

• Journal of Ocean Engineering and Technology
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• v.34 no.1
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• pp.26-36
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• 2020

An extreme value analysis of metocean data which include wave, wind, and current data is a prerequisite for the operation and survival of offshore structures. The purpose of this study was to provide information about the return wave, wind, and current values for the Barents Sea using extreme value analysis. Hindcast datasets of the Global Reanalysis of Ocean Waves 2012 (GROW2012) for a waves, winds and currents were obtained from the Oceanweather Inc. The Gumbel distribution, 2 and 3 parameters Weibull distributions and log-normal distribution were used for the extreme value analysis. The least square method was used to estimate the parameters for the extreme value distribution. The return values, including the significant wave height, spectral peak wave period, wind speed and current speed at surface, were calculated and it will be utilized to design offshore structures to be operated in the Barents Sea.

• ETRI Journal
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• v.33 no.6
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• pp.949-952
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• 2011

In this letter, a simplified suboptimum receiver based on soft-limiting for the detection of binary antipodal signals in non-Gaussian noise modeled as a generalized normal-Laplace (GNL) distribution combined with Gaussian noise is presented. The suboptimum receiver has low computational complexity. Furthermore, when the number of diversity branches is small, its performance is very close to that of the Neyman-Pearson optimum receiver based on the probability density function obtained by the Fourier inversion of the characteristic function of the GNL-plus-Gaussian distribution.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.1399-1406
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• 2009

Probability distribution of geotechnical properties is very useful information and it is used for evaluating the geotechnical properties itself and calculating probability of failure. In this study, probability distribution of compression index, recompression index, and void ratio are evaluated, and analysis results show that all property distributions satisfy normal and log-normal distribution.

• Journal of Applied Reliability
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• v.14 no.1
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• pp.45-51
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• 2014

Thermal shock tests at two stress levels were performed to see the life (cycles) of LPF ASSY (low pass filter assembly) at normal stress level. In this case Coffin-Manson relationship is generally used to describe the relationship between the temperature difference and the life, together with the Weibull distribution describing the life at each stress level. So for given data Coffin-Manson is fitted to predict the life at normal stress level. However, different types of models are appropriate for this type of test. Hence, a more appropriate model such as General log-linear model which can also incorporate the duration at the highest and lowest temperatures and acceleration time will be introduced.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.4
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• pp.17-27
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• 2011

The coupon issued by Korail (Korail's coupon) is characterized by the properties such as a discount rate, an issuing region, a selling region, and a practically discounted rate. The purpose of this study is to investigate their impacts on the redemption time using Log-Normal distribution, and to derive managerial implications for improving Korail's discount program. The result showed that the redemption time was shorter or longer depending a discount rate, an issuing region, a selling region, and a practically discounted rate.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1829-1831
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• 2012

Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.777-777
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• 2005

• Water for future
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• v.7 no.2
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• pp.99-106
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• 1974

The records of wave heights which were observed at Muk ho and Po hang of the East Coast of Korea were analized by several probility functions. The exponential 2 parameter distribution was found as the best fit probability function to the historical distribution of wave heights by the test of goodness of fit. But log-normal 2 parameter and log-extremal type A distributions were also fit to the historical distribution, especially in the Smirnov-Kolmogorov test. Therefore, it can't be always regarded that those two distributions are not fit to the wave heiht's distribution. In the test of goodness of fit, the Chi-Square test gave very sensitive results and Smirnov-Kolmogorov test, which is a distribution free and non-parametric test, gave more inclusive results. At the next stage, the inter-relationship between the mean and the one-third wave heights, the mean and the one-=tenth wave heights, the one-third and the one-tenth wave heights, the one-third and the highest wave heights were obtained and discussed.