• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.173-177
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• 2010

It is well known that if the parent distribution has a nonnegative support and has increasing failure rate, then all the order statistics have increasing failure rate (IFR). The result is not necessarily true in the case of bivariate distributions with dependent structures. In this paper we consider a symmetric bivariate exponential distribution and show that, two marginal distributions are IFR and the distributions of the minimum and maximum are constant failure rate and IFR, respectively.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.193-198
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• 2005

This paper proposes a new method to handle transmission line losses using loss distribution factors (LDF) rather than marginal loss factors (MLF) in electricity market operation. Under a competitive electricity market, the bidding data are adjusted to reflect transmission line losses. To date the most proposed approach is using MLFs. The MLFs are reflected to bidding prices and market clearing price during the trading and settlement of the electricity market. In the proposed algorithm, the LDFs are reflected to bidding quantities and actual generations/ loads. Computer simulations on a 9-bus sample system will verify the effectiveness of the algorithm proposed. Moreover, the proposed approach using LDFs does not make any payments residual while the approach using MLFs induces payments residual.

• Journal of Periodontal and Implant Science
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• v.49 no.3
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• pp.185-192
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• 2019

Purpose: Implant wall thickness and the height of the implant-abutment interface are known as factors that affect the distribution of stress on the marginal bone around the implant. The goal of this study was to evaluate the long-term effects of supracrestal implant placement and implant wall thickness on maintenance of the marginal bone level. Methods: In this retrospective study, 101 patients with a single implant were divided into the following 4 groups according to the thickness of the implant wall and the initial implant placement level immediately after surgery: 0.75 mm wall thickness, epicrestal position; 0.95 mm wall thickness, epicrestal position; 0.75 mm wall thickness, supracrestal position; 0.95 mm wall thickness, supracrestal position. The marginal bone level change was assessed 1 day after implant placement, immediately after functional loading, and 1 to 5 years after prosthesis delivery. To compare the marginal bone level change, repeated-measures analysis of variance was used to evaluate the statistical significance of differences within groups and between groups over time. Pearson correlation coefficients were also calculated to analyze the correlation between implant placement level and bone loss. Results: Statistically significant differences in bone loss among the 4 groups (P<0.01) and within each group over time (P<0.01) were observed. There was no significant difference between the groups with a wall thickness of 0.75 mm and 0.95 mm. In a multiple comparison, the groups with a supracrestal placement level showed greater bone loss than the epicrestal placement groups. In addition, a significant correlation between implant placement level and marginal bone loss was observed. Conclusions: The degree of bone resorption was significantly higher for implants with a supracrestal placement compared to those with an epicrestal placement.

• The Journal of Korean Academy of Prosthodontics
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• v.39 no.4
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• pp.391-409
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• 2001

Since the early study about the osseointegration, lots of researches have been performed to increase the success rate and the stress around the implant in the jaw bone has been considered as one of the causes of failure. The purpose of this study was to examine the relationship between the implant failure and the stress by analysing the influence of different bone quality and bite force of some foods on the stress distribution around the implant, and to estimate the treatment result according to the bone quality and dietary pattern of patients. Bone quality was divided in 4 groups and models were drawn with the assumption that thread type implant(Nobel Biocare AB, Goteborg, Sweden) of 3.75mm diameter, 13mm length was installed to the bones. Various bite forces were applied to the occlusal surface of superstructure and the stress distributed around the implant were analysed with finite element analysis program. The results were as follows ; 1. The stress was changed proportionally to the bite forces of foods at all measuring points in all load cases. 2. The stress at the marginal bone was higher than that of the other measuring points in all load cases, and it was decreased at the first thread area. 3. The stress at the marginal bone was highest in type IV bone in all load cases. Especially it was twice those of other bone types at the bucco-lingual marginal bone and 50% higher at the mesio-distal marginal bone. 4. The stress at the bucco-lingual sides of the bone around the apical portions of implant showed little differences among the bone types, while type IV bone showed lower stress concentration than the other bone types in the mesio-distal sides. 5. Under the buccal oblique load ($15^{\circ}$ ), the stress at the lingual marginal bone was higher than that of buccal marginal bone, and the difference between the two points was almost same regardless of bone types.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.909-917
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• 2003

Although many classification models have been used to classify binary data, none of the classification models dominates all varying circumstances depending on the number of variables and the size of data(Asparoukhov and Krzanowski (2001)). This paper proposes a classification model which uses information on marginal distributions of sub-variables and its maximum entropy distribution. Classification experiments by using simulation are discussed.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.505-511
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• 2007

In this paper, we examine the Markov chain $\{X_k,\;N_k;\;k=0,\;1,...$. We show that the marginal steady state distribution of Xk is discrete phase type. The implication of this result is that the queue length distribution of phase type for large number of examples where this Markov chain is applicable and shows a queueing application by matrix geometric methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.1-3
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• 2009

Recently, Carlsson, Full\acute{e}$r and Majlender [1] presented the concept of possibilitic correlation representing an average degree of interaction between marginal distribution of a joint possibility distribution as compared to their respective dispersions. They also formulated the weak and strong forms of the possibilistic Cauchy-Schwarz inequality. In this paper, we define a new probability measure. Then the weak and strong forms of the Cauchy-Schwarz inequality are immediate consequence of probabilistic Cauchy-Schwarz inequality with respect to the new probability measure.

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.59-79
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• 2021

Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.161-171
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• 2008

This study discusses Johnson's $S_U$-normal distribution capturing a wide range of non-normality in various regression models. We provide the likelihood inference using Johnson's $S_U$-normal distribution, and propose a likelihood ratio (LR) test for normality. We also apply the $S_U$-normal distribution to the binary and censored regression models. Monte Carlo simulations are used to show that the LR test using the $S_U$-normal distribution can be served as a model specification test for normal error distribution, and that the $S_U$-normal maximum likelihood (ML) estimators tend to yield more reliable marginal effect estimates in the binary and censored model when the error distributions are non-normal.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.165-172
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• 1998

This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.