• 한국농공학회지
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• 제40권2호
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• pp.59-68
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• 1998

This study was conducted to derive optimal design floods by generalized gamma distribution model of the annual maximum series at eight watersheds along Geum, Yeongsan and Seomjin river systems. Design floods obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model were compared by the relative mean errors and graphical fit along with 95% confidence limits plotted on gamma probability paper. The results were analyzed and summarized as follows. 1. Basic statistics and parameters were calculated by the generalized gamma distribution model using different methods for parameters. 2. Design floods according to the return periods were obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model. 3. It was found that design floods derived by sundry averages method for parameters and Cunnane method for plotting position in the generalized gamma distribution are much closer to those of the observed data in comparison with those obtained by the other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4. Reliability of design floods derived by sundry averages method in the generalized gamma distribution was acknowledged within 95% confidence interval.

• 한국ITS학회 논문지
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• 제8권4호
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• pp.28-32
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• 2009

본 논문은 DFT기반의 단일마이크 음성향상 방식에 적용된 두 종류의 generalized-Gamma 분포기반의 음성추정 알고리즘을 비교한다. 음성향상 방식으로서는 최소잡음성분에 의한 회귀적인 평균스펙트럼 값으로부터 유도되는 잡음 추정을 각각 $\kappa$=1인 경우와 $\kappa$=2인 경우의 Gamma 분포를 이용한 음성추정 기법에 결합하여 음질을 향상시켰다. 각 방식에 의해 향상된 음성신호를 자동차 환경에서의 음성인식에 적용하여 그 성능을 비교하였다.

• 한국ITS학회 논문지
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• 제8권3호
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• pp.64-70
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• 2009

본 논문은 잡음에 강인한 음성인식 성능을 획득하기 위해 generalized Gamma 분포기반의 음성향상 기법을 제안한다. 우수한 음성향상을 위해서 제안된 방식에서는 generalized Gamma분포와 spectral gain floor를 이용한 음성추적 기법에 스펙트럼 최소잡음성분에 의한 희귀적인 평균 스펙트럼 값으로부터 유도되는 잡음추정을 결합하여 음질을 향상시켜 음성인식에 적용하였다. Spectral component, spectral amplitude 그리고 log spectral amplitude에 기반하여 제안된 음성향상 기법을 잡음환경에서의 음성인식에 적용하여 그 성능을 측정하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제13권5호
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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.

• 한국관개배수논문집
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• 제5권1호
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• pp.32-46
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• 1998

This study was conducted to derive optimal design floods by generalized gamma distribution model of the annual maximum series at six watersheds along Han and Nag Dong river systems. Design floods obtained by different methods for estimation of parameters

• Journal of the Korean Statistical Society
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• 제36권1호
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• pp.93-109
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• 2007

Gamma distributions are some of the most popular models for hydrological processes. In this paper, a very flexible family which contains the gamma distribution as a particular case is introduced. Evidence of flexibility is shown by examining the shape of its pdf and the associated hazard rate function. A comprehensive treatment of the mathematical properties is provided by deriving expressions for the nth moment, moment generating function, characteristic function, Renyi entropy and the asymptotic distribution of the extreme order statistics. Estimation and simulation issues are also considered. Finally, a detailed application to drought data from the State of Nebraska is illustrated.

• International Journal of Reliability and Applications
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• 제4권3호
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• pp.97-111
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• 2003

By applying Theorem 2.6.4 (Fang and Zhang, 1990, p.66) the dispersion matrix of a multivariate power exponential (MPE) distribution is derived. It is shown that the MPE and the gamma distributions are related and thus the MPE and chi-square distributions are related. By extending Fang and Xu's Theorem (1987) from the normal distribution to the Univariate Power Exponential (UPE) distribution an explicit expression is derived for calculating the probability of an UPE random variable over an interval. A representation of the characteristic function (c.f.) for an UPE distribution is given. Based on the MPE distribution the probability density functions of the generalized non-central chi-square, the generalized non-central t, and the generalized non-central F distributions are derived.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.123-130
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• 1997

This paper presents a generalized expansion method for calculating reliability index in power generation systems. This generalized expansion with a gamma distribution is a very useful tool for the approximation of capacity outage probability distribution of generation system. The well-known Gram-Charlier expansion and Legendre series are also studied in this paper to be compared with this generalized expansion using a sample system IEEE-RTS(Reliability Test System). The results show that the generalized expansion with a composite of gamma distributions is more accurate and stable than Gram-Charlier expansion and Legendre series as addition of the terms to be expanded.

• 한국농공학회지
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• 제39권3호
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• pp.83-95
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• 1997

This study was conducted to derive optimal design floods by Gamma distribution models of the annual maximum series at eight watersheds along Geum , Yeong San and Seom Jin river Systems, Design floods obtained by different methods for evaluation of parameters and for plotting positions in the Gamma distribution models were compared by the relative mean errors and graphical fit along with 95% confidence interval plotted on Gamma probability paper. The results were analyzed and summarized as follows. 1.Adequacy for the analysis of flood flow data used in this study was confirmed by the tests of Independence, Homogeneity and detection of Outliers. 2.Basic statistics and parameters were calculated by Gamma distribution models using Methods of Moments and Maximum Likelihood. 3.It was found that design floods derived by the method of maximum likelihood and Hazen plotting position formular of two parameter Gamma distribution are much closer to those of the observed data in comparison with those obtained by other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4.Reliability of derived design floods by both maximum likelihood and method of moments with two parameter Gamma distribution was acknowledged within 95% confidence interval.

• 통합자연과학논문집
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• 제7권2호
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• pp.138-144
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• 2014

Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference where we calculate the posterior distribution using a noninformative prior distribution, and also in an example of metric functions in geometry. To estimate parameters in a distribution, we can use the Fisher information matrix. The more the number of parameters increases, the more its matrix form gets complicated. In this paper, by using Mathematica programs we derive the Fisher information matrix for 4-parameter generalized gamma distribution which is used in reliability theory.