• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.309-322
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• 2023

The Hawkes process is a point process with self-exciting characteristics. It has been mainly used to describe seismic phenomena in which aftershocks occur due to the main earthquake. Recently, it has been used to explain various phenomena with self-exciting properties, such as the spread of infectious diseases and the spread of news on SNS. The Hawkes process can be flexibly modified according to the characteristics of events by using various types of excitation functions. Since it is difficult to implement a maximum likelihood estimator numerically, estimation methods have been improved until recently. In this paper, the conditional intensity function and excitation function are explained to describe the Hawkes process. Then, existing examples of Hawkes processes used in seismic, epidemiological, criminal, and financial fields are described and estimation methods are introduced. I analyze earthquakes that occurred in gyeongsang-do, Korea from November 2017 to December 2022, using R package ETAS.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.363-376
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• 2017

The insurance market is saturated and its growth engine is exhausted; consequently, the insurance industry is now in a low growth period with insurance companies that face a fierce competitive environment. In such a situation, it will be an important issue to find the probability distributions that can explain the flow of insurance claims, which are the basis of the actuarial calculation of the insurance product. Insurance claims are generally known to be well fitted by lognormal distributions or Pareto distributions biased to the left with a thick tail. In recent years, skew normal distributions or skew t distributions have been considered reasonable distributions for describing insurance claims. Cooray and Ananda (2005) proposed a composite lognormal-Pareto distribution that has the advantages of both lognormal and Pareto distributions and they also showed the composite distribution has a higher fitness than single distributions. In this paper, we introduce new composite distributions based on skew normal distributions or skew t distributions and apply them to Danish fire insurance claim data and US indemnity loss data to compare their performance with the other composite distributions and single distributions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.445-452
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• 2015

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log and power intensity function (log linear, log power and exponential power), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure, using real data set for the sake of proposing log and power intensity function, was employed. This analysis of failure data compared with log and power intensity function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• Korea journal of population studies
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• v.26 no.1
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• pp.31-57
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• 2003

This study is intended to examine (l)whether the value of son-for example, old age security and succession of family lineage- causing son preference in the traditional society can be explained at the individual level, (2)whether women without son in the son preference country continue her childbearing until having at least one son or give up the desire of having a son at a certain level. To accomplish these purposes, the 1974 Korean National Fertility Survey data are analyzed by the quadratic hazard models controlling unobserved heterogeneity. Unlike ordinary regression model, even omitted variables that affect hazard rates and are uncorrelated with the included independent variables can distort the parameter estimates in the hazard model. Therefore the nonparametric maximum likelihood estimator(NPMLE) of a mixing distribution developed by Heckman and Singer is used to control unobserved heterogeneity. Based on the statistical result in this study, the value of son causing son preference is determined at the societal level, not at the individual level. And Korean women without a son did not continue endlessly childbearing during child bearing ages until having a son. In general, they gave up the desire having a son when she had born six daughters continuously. Thus, 30-40 years ago, the number of daughters that women without a son giving up the desire of son was six, which is about the level of total fertility rate during 1960s. In these days, we can often see many women who have only two or three daughters and do not any son. This means that the level of giving up the desire of son, which is one factor representing the strength of son preference, becomes lower. If the strength of son preference did not become much weaker, then the fertility rates in Korea could not reach the below replacement level.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.2
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• pp.77-84
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• 2019

Objectives : The Illness Intrusiveness Rating Scale (IIRS) is a well-validated self-report instrument for assessing negative impact of chronic illness and/or adverse effects of its treatment on everyday life domains. Although extensive literature probed its psychometric properties in medical illness, little attention was paid for its validity for psychiatric population. This study aimed to test factorial structure of the Korean Version of the IIRS (IIRS-K) in a consecutive sample of psychiatric outpatients. Methods : Data set of 307 first-visit patients of psychiatric clinic at Guri Hanyang univ. Hospital were used. Exploratory and confirmatory factor analysis, internal consistency were tested in IIRS-K. We also checked Spearman's correlation analysis between IIRS-K, Zung's self-report anxiety scale and Zung's self-report depression scale. Results : 76.9% of the patients were with anxiety disorder and depressive disorder. The principal component factor analysis of the IIRS-K extracted three-factor structure accounted for 63.2% of total variance that was contextually similar to the original English version. This three-factor solution showed the best fit when tested confirmatory factor analysis compared to the original IIRS, two-factor model of IIRS-K suggested from medical outpatients, and one-factor solution. The IIRS-K also showed good internal consistency (Cronbach's α=0.90) and good convergent validity with anxiety and depression scales. Conclusions : The IIRS-K showed the three-factor structure that was similar but not identical to original version. Overall, this study proved factorial validity of the IIRS-K and it can be used for Korean clinical population.