• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.105-120
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• 2015

A large family of distributions arising from distributions of ordered data is proposed which contains other models studied in the literature. This extension subsume many cases of weighted random variables such as order statistics, records, k-records and many others in variety. Such a distribution can be used for modeling data which are not identical in distribution. Some properties of the theoretical model such as moment, mean deviation, entropy criteria, symmetry and unimodality are derived. The proposed model also studies the problem of parameter estimation and derives maximum likelihood estimators in a weighted gamma distribution. Finally, it will be shown that the proposed model is the best among the previously introduced distributions for modeling a real data set.

• 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 KIEE Conference
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• 2001.11b
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• pp.371-373
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• 2001

In this paper, we present 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. Daily load patterns are classified by two methods dependent upon possession information. In case we possess daily load profiles make use of K-mean algorithm and in case we have not daily load profiles, make use of customer information of KEPCO. As the parameters of the load pattern classification, we use are daily load profiles and customer information of each distribution transformers. Data management system is used for NT oracle. We can present peak load magnitude, initial load magnitude and peak load duration for daily load patterns by 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. We think that this paper contributes to enhancing the distribution transformer overload criterion.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.129-142
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• 2017

In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1399-1412
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• 2016

We compare many normality tests consisting of different sources of information extracted from the given data: Anderson-Darling test, Kolmogorov-Smirnov test, Cramervon Mises test, Shapiro-Wilk test, Shaprio-Francia test, Lilliefors, Jarque-Bera test, D'Agostino' D, Doornik-Hansen test, Energy test and Martinzez-Iglewicz test. For the purpose of comparison, those tests are applied to the various types of data generated from skewed distribution, unsymmetric distribution, and distribution with different length of support. We then summarize comparison results in terms of two things: type I error control and power. The selection of the best test depends on the shape of the distribution of the data, implying that there is no test which is the most powerful for all distributions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.3
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• pp.219-223
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• 2016

DC microgrid system is attracted attention in the world, because DC distribution system is more energy efficient than AC distribution system. To analyse the contribution effects of distributed generation(DG) in LVDC distribution system through modeling the Rectifier, DC/DC converter, Energy Storage System(ESS) and Photovoltaic(PV). using PSCAD/EMTDC. This paper analyses fault response characteristics in LVDC distribution system according to the interconnection and islanding operation of DG. Based on research results on the paper, direction for development of fault current reduction method for LVDC distribution system is suggested.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.215-230
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• 2016

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the $Cram{\acute{e}}r-von$ Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by $G{\ddot{u}}ven$ and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.239-259
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• 2019

The transmuted generalized extreme value (TGEV) distribution was first introduced by Aryal and Tsokos (Nonlinear Analysis: Theory, Methods & Applications, 71, 401-407, 2009) and applied by Nascimento et al. (Hacettepe Journal of Mathematics and Statistics, 45, 1847-1864, 2016). However, they did not give explicit expressions for all the moments, tail behaviour, quantiles, survival and risk functions and order statistics. The TGEV distribution is a more flexible model than the simple GEV distribution to model extreme or rare events because the right tail of the TGEV is heavier than the GEV. In addition the TGEV distribution can adjusted various forms of asymmetry. In this article, explicit expressions for these measures of the TGEV are obtained. The tail behavior and the survival and risk functions were determined for positive gamma, the moments for nonzero gamma and the moment generating function for zero gamma. The performance of the maximum likelihood estimators (MLEs) of the TGEV parameters were tested through a series of Monte Carlo simulation experiments. In addition, the model was used to fit three real data sets related to financial returns.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.725-742
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• 2021

The aim of this article is to estimate the coefficient bounds of certain subclasses of analytic functions. We claim that this is a novel and unique effort in combining the coefficient functional along with the new domains and the probability distributions which have not been found or are available in the literature of coefficients bounds. Here the authors analyze these bounds in the special domains associated with exponential function and sine function. Further we obtain Fekete-Szegö inequalities for the defined subclasses of analytic functions defined through Poisson distribution series and Pascal distribution series.

• Journal of the Korean Society of Visualization
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• v.19 no.2
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• pp.32-40
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• 2021

Vapor-driven solutal Marangoni flow is governed by the concentration distribution of solutes on a liquid-gas interface. Typically, the flow structure is investigated by particle image velocimetry (PIV). However, to develop a theoretical model or to explain the working mechanism, the concentration distribution of solutes at the interface should be known. However, it is difficult to achieve the concentration profile theoretically and experimentally. In this paper, to find the concentration distribution of solutes around 2D droplet, the reverse tracking method with an artificial neural network based on PIV data was performed. Using the method, the concentration distribution of solutes around a 2D droplet was estimated for actual flow data from PIV experiment.