• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.753-758
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• 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
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• v.30 no.1
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• pp.95-102
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• 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.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.27-36
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• 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
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• v.31 no.4
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• pp.475-484
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• 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.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.533-540
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• 1997

일반화 감마분포(generalized gamma distribution)에서 지표모수(index parameter)에 대한 추론은 생존시간(lifetime)과 관련한 모형의 선택문제에서 매우 중요하다. 이에 대한 정확한(exact) 추론법은 알려져 있지 않다. 본 연구에서는 이에 대한 점근적(asymptotic) 검정법으로 소표본에서도 우도비 검정에 비해 효율이 뛰어난 Bartlett 검정을 제안하고, 이의 요율적 수행을 위한 대체 모형으로 부터의 누율계산(cumulant computation) 법을 제시하였다. 또한 실제자료에 대해 본 논문에서 제시한 누율계산과정을 이용하여 Bartlett 검정을 실시한 결과 기존의 우도비 검정과는 상당히 큰 차이가 남을 확인하였다. 따라서 모형의 선택 등의 문제에서 제안된 방법은 소표본의 경우에 더욱 효율적이라 할 수 있다.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1069-1076
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• 2014

Rainfall weather patterns have changed due to global warming and sudden heavy rainfalls have become more frequent. Economic loss due to heavy rainfall has increased. We study the generalized Pareto distribution for modelling rainfall in Seoul based on data from 1973 to 2008. We use several priors including Jeffrey's noninformative prior and Gibbs sampling method to derive Bayesian posterior predictive distributions. The probability of heavy rainfall has increased over the last ten years based on estimated posterior predictive distribution.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.435-442
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• 1993

For the generalized gamma distribution, exact inferences about quantiles need many computations involving complicated numerical integrations. This paper suggests approximate confidence intervals which are easily obtained by considering the alternative location-scale model. Also, these intervals are very accurate even for small sample size. Approximate confidence intervals about quantiles in the lognormal distribution are also considered. With type 2 censoring data, approximate confidence intervals can also be obtained directly by the suggested methods.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.753-763
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• 1997

컴퓨터의 발전에 따른 MCMC를 비동질적 포아송 과정에 이용하였다. 베이지안 추론에서 조건부 분포를 가지고 사후분포를 결정하는데 있어서의 계산 문제를 고려하였다. 특히 분포가 이중지수, 곰페르츠, 랄리, 감마, 그리고 검벨인 일반 순서통계량 모형에 대하여 깁스 샘플링과 메트로폴리스 알고리즘을 활용한 베이지안 계산과 모형선택을 제시하였다.

• Journal of the Economic Geographical Society of Korea
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• v.24 no.4
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• pp.411-424
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• 2021

The purpose of this study is to analyze the location characteristics of convenience stores, a consumption industry that forms a new retail environment and implements unattended, and reveals the geographic factors that affect its location. For this purpose, we first examine the growth and regional distribution of manned convenience stores and then construct a gamma generalized linear regression model that explains the distribution of the unmanned convenience stores as well as the manned and unmanned combined convenience stores. As the result, it was observed that the unmanned convenience stores and the unmanned discount stores are located close to public transportation facilities and they have relatively little movement of the population but they are distributed in areas with a higher density of young residential population and densely distributed retail stores and restaurants. The effects of demographic factors on the location of the unmanned convenience stores and the unmanned discount stores differed according to the scope and characteristics of their sales items. Our findings provide an empirical basis for subsequent academic research as an initial study that identified geographic factors influencing the selection of opening locations for unmanned stores.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.591-618
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• 2023

This paper evaluates the performance of various distribution assumptions in regression settings for estimating insurance loss. The gamma distribution is commonly used to handle the asymmetry property of loss distribution. However, recent studies highlight the significance of heavy-tailedness in loss distribution. Through an analysis of real home fire insurance data, we compare the effectiveness of different distribution assumptions in regression methods. Our findings show that the choice of parametric distributional assumption is crucial in determining premiums for various insurance products, including "excess of loss insurance" and "limit insurance". Additionally, we discuss practical considerations for applying our results in home fire insurance.