• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.479-493
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• 2012

The inverse Weibull distribution(IWD) is a complementary Weibull distribution and plays an important role in many application areas. In this paper, we develop a Bayesian estimator in the context of record statistics values from the exponentiated inverse Weibull distribution(EIWD). We obtained Bayesian estimators through the squared error loss function (quadratic loss) and LINEX loss function. This is done with respect to the conjugate priors for shape and scale parameters. The results may be of interest especially when only record values are stored.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.101-116
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• 1990

The objectives of this thesis are : first, to estimate the parameters and Pr[X < Y] in the Marshall and Olkin's Bivariate Exponential Distribution ; and secondly, to compare the Bayes estimators of Pr[X < Y] with maximum likelihood estimator of Pr[X < Y] in the Marshall and Olkin's Bivariate Exponential Distribution. Through the Monte Carlo Simulation, we observed that the Bayes estimators of Pr[X < Y] perform better than the maximum likelihood estimator of Pr[X < Y] and the Bayes estimator of Pr[X < Y] with gamma prior distribution performs better than with vague prior distribution with respect to bias and mean squared error in the Marshall and Olkin's Bivariate Exponential Distribution.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.5-12
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• 2000

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution and it is shown to be useful in such Bayesian meta-analysis. A general class of skewed elliptical distribution is reviewed and developed. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierarchical selection model and use Markov chain Monte Carlo methods to develop inference for the parameters of interest.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.11a
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• pp.293-295
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• 2004

Public utilities adopt the grounding rules ; class I, class II, class III and special class III, and install the grounding electrodes in distribution facilities. To keep the safety of the human and the facilities, Public utilities also manage the value of ground resistance in distribution system biennially. At present the Hook-On meter is normally used to measure the ground resistance although it has ${\pm}5[%]$ measuring error and it can not measure the exact value when the current is over 1[A]. In addition it is very difficult to use the fall-of-potential method in distribution system. In this paper we propose the new measurement method using ground current of distribution system as the current source.

• IE interfaces
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• v.12 no.3
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• pp.401-405
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• 1999

We present a simulation model to generate the spatial distribution of mobiles in cellular communication network. Three types of spatial distributions are considered; biased, random, and ratio-based distributions. This study also points out and corrects the critical errors performed by Das and Morgera(1997) in getting random location of mobiles. By applying a simple path loss model, the effects of our correction on the signal-to-interference(SIR) ratio are discussed. The numerical results indicate that the variation of SIR in the Das's biased distribution is larger than that of other distributions. As compared with the random distribution, the average SIR error of the biased distribution is 91.1%.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.3
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• pp.176-185
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• 2009

A general flow distribution model and a simple process of numerical analysis, which can be applied to multi-pass systems with manifolds, are presented. A numerical procedure, namely a modified equal pressure method based on the discrete model, was developed to predict flow rates at branch tubes. The predicted pressure distribution agreed well with the previous research with the average error less than 11%. A parametric study was performed to demonstrate the effect on the flow distribution.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.3
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• pp.17-28
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• 2014

The paper deals with the impact of the product distribution and information technology sectors on energy resource use, carbon emissions and economic growth by examining the long-run equilibrium relationships and Granger causal relationships among these variables in South Korea. The quarterly time series data from the first quarter of 1970 to the third quarter of 2010 (163 observations) are collected and retrieved from the Bank of Korea database. The paper examines the long-run equilibrium relationships using cointegration techniques and Granger causality using vector error correction models. Test results indicate a long-run equilibrium relationship exists among these variables. In testing directional causality, both the product distribution and the information technology sectors show direct effects on economic growth but only marginal effects on carbon emissions.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.425-448
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• 2003

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution proposed originally by Chen et al. (1999) and Branco and Dey (2001). These rich classes of models combine the information of independent studies, allowing investigation of variability both between and within studies, and incorporate weight function. Here, the testing for the skewness parameter is discussed. The score test statistic for such a test can be shown to be expressed as the posterior expectations. Also, we consider the detail computational scheme under skewed normal and skewed Student-t distribution using MCMC method. Finally, we introduce one example from Johnson (1993)'s real data and apply our proposed methodology. We investigate sensitivity of our results under different skewed errors and under different prior distributions.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.569-575
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• 2018

Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2280-2285
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• 2008

A general flow distribution model and a simple process of numerical analysis, which can be applied to multi-pass systems with manifolds, are presented. Correlations are derived from the discrete model, and numerically calculated using a modified equal pressure method. The predicted pressure distribution agrees well with the available experimental results of other researchers with the average error less than 2% for 10 branch manifolds, and 4% for 20 branch manifolds. A parametric study is performed to demonstrate the effect on the flow distribution.