• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.509-518
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• 2002

This paper is concerned with semiparametric Bayesian analysis of the proportional intensity regression model of the Poisson process for multiple event time data. A nonparametric prior distribution is put on the baseline cumulative intensity function and a usual parametric prior distribution is given to the regression parameter. Also we allow heterogeneity among the intensity processes in different subjects by using unobserved random frailty components. Gibbs sampling approach with the Metropolis-Hastings algorithm is used to explore the posterior distributions. Finally, the results are applied to a real data set.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.219-231
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• 2006

When the correlation of two random variables is weak, the value of one variable can not be used effectively to predict the other. Even when most of the values are overlapped, it is difficult to find a linear relationship. In this paper, we propose two graphical methods of representing the measures of correlation and independence between two random variables. The first method is used to represent their degree of correlation, and the other is used to represent their independence. Both of these methods are based on the cumulative distribution functions defined in this work.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1240-1243
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• 2016

In this paper, we analyze the queueing performance of cumulative distribution function (CDF)-based opportunistic scheduling over Nakagami-m Markov fading channels. We derive the formula for the average queueing delay and the queue length distribution by constructing a two-dimensional Markov chain. Using our formula, we investigate the queueing performance for various fading parameters.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.629-638
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• 2012

We propose some methods to obtain optimal thresholds and classification functions by using various cutoff criterion based on the bivariate ROC curve that represents bivariate cumulative distribution functions. The false positive rate and false negative rate are calculated with these classification functions for bivariate normal distributions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.301-301
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• 1993

• Journal of Ocean Engineering and Technology
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• v.5 no.2
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• pp.225-225
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• 1991

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.267-270
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• 2002

The evaluation of the cumulative distribution function of the noncentral $\chi^2$ distribution is required in approximate determination of the power of the $\chi^2$ test. This article provides an algorithm for evaluating the noncentral $\chi^2$ distribution function in terms of a single "central" $\chi^2$ distribution function and compared various approximations.ximations.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.183-191
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• 2014

We define a multivariate Cauchy distribution using a probability density function; subsequently, a Ferguson's definition of a multivariate Cauchy distribution can be viewed as a characterization theorem using the characteristic function approach. To clarify this characterization theorem, we construct two dependent Cauchy random variables, but their sum is not Cauchy distributed. In doing so the proofs depend on the characteristic function, but we use the cumulative distribution function to obtain the exact density of their sum. The derivation methods are relatively straightforward and appropriate for graduate level statistics theory courses.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.125-134
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• 2014

Kullback-Leibler (KL) information is a measure of discrepancy between two probability density functions. However, several nonparametric density function estimators have been considered in estimating KL information because KL information is not well-defined on the empirical distribution function. In this paper, we consider the KL information of the equilibrium distribution function, which is well defined on the empirical distribution function (EDF), and propose an EDF-based goodness of fit test statistic. We evaluate the performance of the proposed test statistic for an exponential distribution with Monte Carlo simulation. We also extend the discussion to the censored case.

• Journal of Periodontal and Implant Science
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• v.35 no.2
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• pp.437-448
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• 2005

This study is an analysis of distribution of patients who installed Xive implant in Yonsei University Hospital and types of implant site for about 2 years recall check and cumulative survival rate. 41 implant were used in this study. It shows the conclusion below. 1. Patients at the age of 40s and 50s were 60% of all implant cases and average number of implant was 2.4(man), and 1.9(woman). All cases were operated on mandible, 3 implants on anterior region and 38 implants on posterior region. 2. The major cause of tooth loss is dental caries(48.8%), followed by periodontal disease. 3. Most distribution of bone qaulity for mandibular implant site was type II(65.8%) and bone quantity was type B(75.6%). 4. The majority of implants were those of 11, 13mm in length(95%) and regular diameter in width (64%). 5. The 41(19 persons) Xive implants that were placed in the mandibular anterior and posterior region were all survival and showed a 100% 2 year cumulative survival rate. The results provided us with basic data on patient type, implant distribution, bone condition, and survival rate. We wish that our results coupled with other research data helps assist in the further study for better implant success rates, etc.