• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.487-500
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• 2020

Insurers face increasing demands for cyber liability; entailed in part by a variety of new forms of risk of data breaches. As data breach occurrences develop, our understanding of the volatility in data breach counts has also become important as well as its expected occurrences. Volatility clustering, the tendency of large changes in a random variable to cluster together in time, are frequently observed in many financial asset prices, asset returns, and it is questioned whether the volatility of data breach occurrences are also clustered in time. We now present volatility analysis based on INGARCH models, i.e., integer-valued generalized autoregressive conditional heteroskedasticity time series model for frequency counts due to data breaches. Using the INGARCH(1, 1) model with data breach samples, we show evidence of temporal volatility clustering for data breaches. In addition, we present that the firms' volatilities are correlated between some they belong to and that such a clustering effect remains even after excluding the effect of financial covariates such as the VIX and the stock return of S&P500 that have their own volatility clustering.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.761-769
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• 2018

Simulations are important for survival analyses that deal with censored data. Cox models are widely used in survival analyses, therefore, we investigate how to generate censored data that can simulate the Cox model. Bender et al. (Statistics in Medicine, 24, 1713-1723, 2005) provided a parametric method for generating survival times, but we need to generate censoring times as well as survival times to simulate the censored data. In addition to the parametric method for generating censored data, a nonparametric method is also proposed and applied to a real data set.

• Genomics & Informatics
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• v.20 no.1
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• pp.8.1-8.14
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• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.

• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.393-410
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• 2021

The Korean Long-Term Care Insurance (K-LTCI) provides financial support for long-term care service to people who need various types of assistance with daily activities. As the number of elderly people in Korea is expected to increase in the future, the demand for long-term care insurance would also increase over time. Projection of future expenditure on K-LTCI depends on the number of beneficiaries within the grading system of K-LTCI based on the test scores of applicants. This study investigated the suitability of mixture distributions to the model K-LTCI score distribution using recent empirical data on K-LTCI, provided by the National Health Insurance Service (NHIS). Based on the developed mixture models, the number of beneficiaries in each grade and its variability under the current grading system were estimated by simulation. It was observed that a mixture model is suitable for K-LTCI score distribution and may prove useful in devising a funding plan for K-LTCI benefit payment and investigating the effects of any possible revision in the K-LTCI grading system.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.77-96
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• 2018

A reverse mortgage provides a pension until the death for the insured or last survivor. Long-term risk management is important to estimate the contractual period of a reverse mortgage. It is also necessary to study prediction methods of mortality rates that appropriately reflect the improvement trend of the mortality rate since the extension of the life expectancy, which is the main cause of aging, can have a serious impact on the pension financial soundness. In this study, the Lee-Carter (LC) model reflects the improvement in mortality rates; in addition, multiple life model are also applied to a reverse mortgage. The mortality prediction method by the traditional LC model has shown a dramatic improvement in the mortality rate; therefore, this study suggests mortality projection based on the projection of the skewness for the mortality that has been applied to appropriately reflect the improvement trend of the mortality rate. This paper calculates monthly payments using future mortality rates based on the projection of the skewness of the mortality. As a result, the mortality rates based on this method less reflect the mortality improvement effect than the mortality rates based on a traditional LC model and a larger pension amount is calculated. In conclusion, this method is useful to forecast future mortality trend results in a significant reduction of longevity risk. It can also be used as a risk management method to pay appropriate monthly payments and prevent insufficient payment due to overpayment by the issuing institution and the guarantee institution of the reverse mortgage.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.47-63
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• 2018

This study suggested quantitative models to calculate a royalty rate as an important input factor of the relief from royalty method which has the characteristics of income approach method and market approach method that are generally used in the valuation of intangible assets. This study built a royalty rate regression model by referring to the patent infringement damages cases based on royalties, i.e., by using the royalty rates as a dependent variable and the patent indexes of the corresponding patent right as independent variables. Then, a logistic regression model was constructed by referring to inter-partes review cases of patent rights, i.e. by using not-unpatentable results as a dependent variable and the patent indexes of the corresponding patent right as independent variables. A final royalty rate was calculated by matching the royalty rate from the royalty rate regression model with a not-unpatentable probability from the logistic regression model. The suggested royalty rate was compared with the royalty rate obtained by the traditional methods to check its reliability.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.3
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• pp.319-323
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• 2006

Heritabilities and genetic correlations of economic traits were estimated with a multiple-trait animal model on 5 different strains of Korea Native Chickens (KNC): Red Brown (RB), Yellow Brown (YB), Gray Brown (GB), Black (B) and White (W). The data used for this study were collected from the Daejeon branch of the National Livestock Research Institute and included 11,233 performance records and 12,729 individual animals. DFREML and SAS BASE/STAT packages were used to estimate genetic parameters and descriptive statistics. The estimated heritabilities for strain RB, YB, GB, B and W, respectively, for age at 1st egg were 0.24, 0.27, 0.12, 0.32 and 0.18; for body weight at first egg were 0.39, 0.43, 0.38, 0.52 and 0.57; for body weight at age of 270 days were 0.43, 0.51, 0.30, 0.52 and 0.67; for egg weight at first egg were 0.08, 0.13, 0.07, 0.06 and 0.07; for egg weight at age of 270 days were 0.37, 0.43, 0.22, 0.34 and 0.41; and for number of eggs laid by age of 270 days were 0.24, 0.25, 0.37, 0.36 and 0.30. The genetic and phenotypic correlations were also estimated.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.239-256
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• 2020

Health is an important issue due to increased life expectancy. As a result, the demand for industry and services associated with individual health, health-related programs and services will be facilitated by a method to evaluate and classify the health level of an individual based on various factors. This study suggests a methodology to measure and score an individual health level. A credit scoring model was introduced to implement the categorization of variables, construct a prediction model, and to score individual health level. Cohort DB provided by National Health Insurance Service was used to illustrate overall procedures. It is expected that the suggested model can be utilized in designing and managing health care services as well as other health-related programs.

• Journal of Chest Surgery
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• v.26 no.1
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• pp.24-31
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• 1993

The long term clinical results following valve replacement with Hancock and Carpentier-Edwards bioprostheses were compared between tow valve models and between tow groups totaling 249 patients who were discharged after valve replacement from 1976 to 1986. The two groups of patients were treated with nonrandomized fashion. Follow-up was 87% complete. Cummulative duration of follow-up was 1909 patient-years, with maximum follow-up duration of 15 years. The actuarial survival for 122 patients with Hancock valves was 95.2%[\ulcornerstandard deviation] and 84.4% after 5 and 10 years of follow-up, respectively. Comparable figures for 127 patients undergoing valve replacement with Carpentier-Edwards valves were 87.3% and 76.4%, respectively[p=NS]. The probability of freedom from structural valve deterioration after 5 and 10 years of follow-up was 97.2% and 60.6%, respectively, with Hancock valves and 97.2% and 55.7%, respectively, with Carpentier-Edwards valves[p=NS]. Considering all 249 patients, multivariate [Cox model] regression revealed that ejection fraction was only significant predictor of structural valve deterioration. The probability of freedom from thromboembolism after 5 and 10 years of follow-up was 91.3% and 86.4%, respectively, with Hancock valves and 94.2% and 82.5%, respectively, with Carpentier-Edwards valves[p=NS]. Hence more strict control of anticoagulation should be done on patients with left atrial factors. In summary, there were no significant differences in actuarial survival rate and major valve related complications between tow valve models. These results suggests that its use should be confined to older patients or patients with a contraindication of anticoagulation.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.445-452
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• 2009

Credibility models are actuarial tools to distribute premiums fairly among a heterogeneous group of policyholders. Many existing credibility models can be expressed as special cases of linear mixed effects models. In this paper we propose a nonlinear credibility regression model by reforming the linear mixed effects model through kernel machine. The proposed model can be seen as prediction method applicable in any setting where repeated measures are made for subjects with different risk levels. Experimental results are then presented which indicate the performance of the proposed estimating procedure.