• Magazine of the Korean Society of Agricultural Engineers
• /
• v.40 no.2
• /
• pp.59-68
• /
• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.4
• /
• pp.28-32
• /
• 2009

This paper compares two speech estimators under a generalized Gamma distribution for DFT-based single-microphone speech enhancement methods. For the speech enhancement, the noise estimation based on recursive averaging spectral values by spectral minimum noise is applied to two speech estimators based on the generalized Gamma distribution using $\kappa$=1 or $\kappa$=2. The performance of two speech enhancement algorithms is measured by recognition accuracy of automatic speech recognition(ASR) in car noisy environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.3
• /
• pp.64-70
• /
• 2009

This paper presents a speech enhancement technique based on generalized Gamma distribution in order to obtain robust speech recognition performance. For robust speech enhancement, the noise estimation based on a spectral noise floor controled recursive averaging spectral values is applied to speech estimation under the generalized Gamma distribution and spectral gain floor. The proposed speech enhancement technique is based on spectral component, spectral amplitude, and log spectral amplitude. The performance of three different methods is measured by recognition accuracy of automatic speech recognition (ASR).

• KCID journal
• /
• v.5 no.1
• /
• pp.32-46
• /
• 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 Korea Society of Computer and Information
• /
• v.10 no.6 s.38
• /
• pp.27-36
• /
• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates Per fault. This Paper Proposes reliability model using the generalized gamma distribution, which can capture the monotonic increasing(or monotonic decreasing) nature of the failure occurrence rate per fault. Equations to estimate the parameters of the generalized gamma finite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing shape parameter of the generalized gamma distribution, used to the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the gamma or Weibull model. Analysis of failure data set for the generalized gamma modell, using arithmetic and Laplace trend tests . goodness-of-fit test, bias tests is presented.

• The Korean Journal of Applied Statistics
• /
• v.30 no.1
• /
• pp.95-102
• /
• 2017

Gamma generalized linear models have received less attention than Poisson and binomial generalized linear models. Therefore, many old-established statistical techniques are still used in gamma generalized linear models. In particular, existing literature and textbooks still use approximate estimates for the dispersion parameter. In this paper we study the efficiency of various dispersion parameter estimators in gamma generalized linear models and perform numerical simulations. Numerical studies show that the maximum likelihood estimator and Cox-Reid adjusted maximum likelihood estimator are recommended and that approximate estimates should be avoided in practice.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.39 no.3
• /
• pp.83-95
• /
• 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.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.753-758
• /
• 2004

A generalization of gamma distribution is defined by slightly modifying the form of Kobayashi's generalized gamma function(1991). We define a new extended gamma distribution and study some properties of this distribution.

• The Korean Journal of Applied Statistics
• /
• v.31 no.4
• /
• pp.475-484
• /
• 2018

Gamma generalized linear models are useful for non-negative and skewed responses. However, these models have received less attention than Poisson and binomial generalized linear models. In particular, hypothesis testing for the significance of regression coefficients has not been thoroughly studied. In this paper we assess the performance of various test statistics for gamma generalized linear models based on numerical studies. Our results show that the likelihood ratio test and F-type test are generally recommended and that the partial deviance test should be avoided in practice.

• Proceedings of the Korea Water Resources Association Conference
• /
• 1998.05a
• /
• pp.127-132
• /
• 1998