• ETRI Journal
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• v.27 no.6
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• pp.747-758
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• 2005

The problem of selection among competing models has been a fundamental issue in statistical data analysis. Good fits to data can be misleading since they can result from properties of the model that have nothing to do with it being a close approximation to the source distribution of interest (for example, overfitting). In this study we focus on the preference among models from a family of polynomial regressors. Three decades of research has spawned a number of plausible techniques for the selection of models, namely, Akaike's Finite Prediction Error (FPE) and Information Criterion (AIC), Schwartz's criterion (SCH), Generalized Cross Validation (GCV), Wallace's Minimum Message Length (MML), Minimum Description Length (MDL), and Vapnik's Structural Risk Minimization (SRM). The fundamental similarity between all these principles is their attempt to define an appropriate balance between the complexity of models and their ability to explain the data. This paper presents an empirical study of the above principles in the context of model selection, where the models under consideration are univariate polynomials. The paper includes a detailed empirical evaluation of the model selection methods on six target functions, with varying sample sizes and added Gaussian noise. The results from the study appear to provide strong evidence in support of the MML- and SRM- based methods over the other standard approaches (FPE, AIC, SCH and GCV).

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.609-628
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• 1995

This paper presents a reliability model and a data-analytic procedure for a repairable unit subject to failures due to multiple non-identifiable causes. We regard a failure cause as a state and assume the life distribution for each cause to be exponential. Then we represent the dependency among the causes by a Markov switching model(MSM) and estimate the transition probabilities and failure rates by maximum likelihood(ML) method. The failure data are incomplete due to masked causes of failures. We propose a specific version of EM(expectation and maximization) algorithm for finding maximum likelihood estimator(MLE) under this situation. We also develop statistical procedures for determining the number of significant states and for testing independency between state transitions. Our model requires only the successive failure times of a unit to perform the statistical analysis. It works well even when the causes of failures are fully masked, which overcomes the major deficiency of competing risk models. It does not require the assumption of stationarity or independency which is essential in mixture models. The stationary probabilities of states can be easily calculated from the transition probabilities estimated in our model, so it covers mixture models in general. The results of simulations show the consistency of estimation and accuracy gradually increasing according to the difference of failure rates and the frequency of transitions among the states.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.40-47
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• 2006

Claim history data of rather long period were collected to assess reliability and warranty cost analyses. The data were appropriately organized to be used for further statistical analyses. For each critical component, nonparametric statistical method was applied to obtain reliability plot. Hazard plots of the components in a subsystem or system level were also obtained. Competing risk model was assumed to obtain the performance of the subsystem or system level.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.267-276
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• 2012

Bagai et al. (1989) proposed a distribution-free test for stochastic ordering in the competing risk model, and recently Murakami (2009) utilized a standard saddlepoint approximation to provide tail probabilities for the Bagai statistic under finite sample sizes. In the present paper, we consider the Gaussian-polynomial approximation proposed in Ha and Provost (2007) and compare it to the saddlepoint approximation in terms of approximating the percentiles of the Bagai statistic. We make numerical comparisons of these approximations for moderate sample sizes as was done in Murakami (2009). From the numerical results, it was observed that the Gaussianpolynomial approximation provides comparable or greater accuracy in the tail probabilities than the saddlepoint approximation. Unlike saddlepoint approximation, the Gaussian-polynomial approximation provides a simple explicit representation of the approximated density function. We also discuss the details of computations.

• Korean Journal of Social Welfare Studies
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• v.45 no.2
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• pp.233-261
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• 2014

There are two competing models explaining the causal relationship of depression and self-esteem, and they are cognitive vulnerability model and the scar model. Cognitive vulnerability model explains that low self-esteem poses as a risk factor for development of depressive symptoms/depression while the scar model asserts that the experiences of depression scars the cognitive function of individuals, resulting in negative self-perception. This study was set out to test two models on Korean adults, and to identify factors that are associated with depression and self-esteem relationship. The first four waves (wave 1~4) of the Korea Welfare Panel Study (KOWEPS) were used for analyses, and latent growth curve modeling was employed to examine the relationship. The findings show that the relationship was reciprocal, one affecting the growth trajectory of another over a four year period. Furthermore, education, poverty status, health status, and satisfaction with social relationships were found to be significantly associated with both depression and self-esteem trajectories. Implications for practice and theory are provided.

• Korean Business Review
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• v.1
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• pp.115-134
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• 1987

The increased number of organized employees and amount of collective bargaining in the public sector has caused many industrial relations students to pay attention to the compulsory arbitration mechanism. Some of these have criticized the compulsory arbitration on the grounds that it tends to replace collective bargain ing itself. They argue that each party lacks the incentive to concede and compromise that is so necessary in reaching agreements as long as the threat and/or use of strike is unavailable to them. On the other hand, the proponents of the compulsory arbitration maintain that compulsory arbitration carries out a strike like function by imposing the cost of disagreement. This paper is primarily concerned with these contradictory issues. More particularly, an attempt is made to analyze the impact of the compulsory arbitration mechanism upon the collective bargaining process by developing a bargaining model with explicit considerations of the determinants of the concession behavior of each party as a function of the cost of disagreement and the risk willingness relationship between the parties. The analysis in this paper leads to a synthesis of the above competing arguments, and shows that those contradictory views on the effect of the compulsory arbitration are mainly due to their failure to con sider the concession process.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.652-655
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• 2007

Due to stagnation of domestic market, increasing number of domestic construction companies started to make inroads into foreign market recently. Yet compared to domestic market, there are much more risks in the foreign market which companies may confront. So deliberate and rational decision making skills are required. Accordingly, there has been many researches which analyzed the risk of individual markets and also studies covering decision support models. In this study, we suggest a model concerning financial issues when branching out into a new market, specially in the construction companies' point of view. For this we used a real options game which shows real competition status of a new market and deduced a feature of that market, Upon these results, we also suggest a model which helps firms to decide whether investing in the expansion is smart action or not. The model developed in this study is made in specific circumstances of limited conditions. The future study makes more realistic models considering subjects like disproportion in information and generalization of competing companies.

• Analyses & Alternatives
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• v.5 no.2
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• pp.77-105
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• 2021

Natural gas consumption in Asia is growing at fast tempo because of various factors such as economic growth in the region, urbanization, coal-to-gas switch at power and industry sector. Due to geographical characteristics and lack of international pipeline connections between countries in the continent, majority of natural gas exported to Asian consumers is transported by tankers on the sea in the form of liquefied natural gas. As Asian market is the most lucrative market with the fastest demand growth, the competitions between LNG sellers for market share in Asian market are strengthening. The competitions accelerated, especially after the introduction of large volume of incremental supply into the market by new exporters from the U.S., Australia, and Russia. Cheniere Energy, the first exporter of liquefied natural gas (LNG) in the lower 48 states of U.S. has not adopted the traditional price formation mechanism and business model. Traditionally, prices of long-term LNG contracts have been indexed to the price of competing fuels, such as crude oil. The company adopted a pricing mechanism and business model based on a cost-plus system. Cheniere Energy opted for the safer and the risk-free pricing system, that annually guarantees a fixed amount of revenue to the seller. The company earns the same amount of money, regardless of natural gas price dynamics in the domestic and international market, but possibly with less revenue. However, by introducing and successfully implementing the safer and risk- free business model, Cheniere Energy, a company of a relatively smaller size in comparison with major oil and gas companies, became an example to other smaller-sized companies in the U.S. The company's business model demonstrated how to enter and operate LNG business amid increasing competitions among sellers in the U.S. and international market.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.1985-1995
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• 2021

Objective: Although the liver-to-spleen volume ratio (LSVR) based on CT reflects portal hypertension, its prognostic role in cirrhotic patients has not been proven. We evaluated the utility of LSVR, automatically measured from CT images using a deep learning algorithm, as a predictor of hepatic decompensation and transplantation-free survival in patients with hepatitis B viral (HBV)-compensated cirrhosis. Materials and Methods: A deep learning algorithm was used to measure the LSVR in a cohort of 1027 consecutive patients (mean age, 50.5 years; 675 male and 352 female) with HBV-compensated cirrhosis who underwent liver CT (2007-2010). Associations of LSVR with hepatic decompensation and transplantation-free survival were evaluated using multivariable Cox proportional hazards and competing risk analyses, accounting for either the Child-Pugh score (CPS) or Model for End Stage Liver Disease (MELD) score and other variables. The risk of the liver-related events was estimated using Kaplan-Meier analysis and the Aalen-Johansen estimator. Results: After adjustment for either CPS or MELD and other variables, LSVR was identified as a significant independent predictor of hepatic decompensation (hazard ratio for LSVR increase by 1, 0.71 and 0.68 for CPS and MELD models, respectively; p < 0.001) and transplantation-free survival (hazard ratio for LSVR increase by 1, 0.8 and 0.77, respectively; p < 0.001). Patients with an LSVR of < 2.9 (n = 381) had significantly higher 3-year risks of hepatic decompensation (16.7% vs. 2.5%, p < 0.001) and liver-related death or transplantation (10.0% vs. 1.1%, p < 0.001) than those with an LSVR ≥ 2.9 (n = 646). When patients were stratified according to CPS (Child-Pugh A vs. B-C) and MELD (< 10 vs. ≥ 10), an LSVR of < 2.9 was still associated with a higher risk of liver-related events than an LSVR of ≥ 2.9 for all Child-Pugh (p ≤ 0.045) and MELD (p ≤ 0.009) stratifications. Conclusion: The LSVR measured on CT can predict hepatic decompensation and transplantation-free survival in patients with HBV-compensated cirrhosis.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.777-789
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• 2020

COVID-19 has been rapidly spread world wide since late December 2019. In this paper, our interest is to estimate distribution of incubation time defined as period between infection of virus and the onset. Due to the limit of accessibility and asymptomatic feature of COVID-19 virus, the exact infection and onset time are not always observable. For estimation of incubation time, interval censoring technique is implemented. Furthermore, a competing risk model is applied to estimate the case fatality and cure fraction. Based on the result, the mean incubation time is about 5.4 days and the fatality rate is higher for older and male patient and the cure rate is higher at younger,female and asymptomatic patient.