• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.305-317
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• 2004

We construct the empirical Bayes (EB)estimation of the parameter in two-side truncated distribution families with asymmetric Linex loss using negatively associated (NA) samples. The asymptotical optimality and convergence rate of the EB estimation is obtained. We will show that the convergence rate can be arbitrarily close to $O(n^{-q}),\;q\;=\;{\lambda}s(\delta\;-\;2)/\delta(s\;+\;2)$.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.607-617
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• 2012

The goodness-of-fit test for multivariate normal distribution is important because most multivariate statistical methods are based on the assumption of multivariate normality. We propose goodness-of-fit test statistics for multivariate normality based on the modified squared distance. The empirical percentage points of the null distribution of the proposed statistics are presented via numerical simulations. We compare performance of several test statistics through a Monte Carlo simulation.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.517-529
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• 2016

This study compares the inverse transform and the composition methods for generating data from the Lindley distribution. The expression for the inverse of the distribution function for the Lindley distribution does not exist in closed form. Hence, authors of many empirical studies on the Lindley distribution used methods for generating Lindley variates other than the inverse transform. We generated data from the Lindley distribution using the inverse transform approach by obtaining the Lindley variates numerically; we also generated data from this distribution using the composition approach. Following the generation of the Lindley variates using these two methods, we compare some statistical properties of the estimates of the Lindley model parameters based on the generated data. We conclude that the two methods produce similar results.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.349-361
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• 2009

In this paper, we derive the approximate maximum likelihood estimators of the shape parameter and the scale parameter in a Weibull distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We develop three modified empirical distribution function type tests for the Weibull distribution based on multiply Type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

• The Korean Journal of Ceramics
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• v.6 no.3
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• pp.240-244
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• 2000

The three-dimensional orientation distribution function of a conical shaped tungsten liner prepared by the thermo-mechanical forming process was analyzed by 1.525$\AA$ neutrons to carry out the Rietveld refinement. The pole figure data of three reflections, (110)(220) and (211) were measured. The orientation distribution functions for the normal and radial directions were calculated by the WIMV method. The inverse pole figures of the normal and radial directions were obtained from their orientation distribution functions. The Rietveld refinement was performed with the RIETAN program that was slightly modified for the description of preferred orientation effect. We could successfully do the Rietveld refinement of the strongly textured tungsten liner by applying the pole density of each reflection obtained from the inverse pole figure to the calculated diffraction pattern. The correction method of preferred orientation effect based on the inverse pole figures showed a good improvement over the semi-empirical texture correction based on the direct usage of simple empirical functions.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.33-42
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• 1999

A method of detecting influential observations in principal factor analysis is suggested. it is based on a perturbation of the empirical distribution function and an adoption of the local influence method. An illustrative example is given.

• Journal of Distribution Science
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• v.17 no.1
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• pp.21-31
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• 2019

Purpose - As the market economy deepens, the issue of social equity caused by income distribution becomes more and more significant. Therefore, this paper attempts to exploit the determinants of income distribution in terms of macroeconomics. Research design, data, and methodology - The data set from 1990 to 2017 will be used to conduct an empirical analysis under a menu of econometric approaches such as vector autoregressive model and impulse response function. The income distribution and other macroeconomic variables such as foreign direct investment and employment will be used to conduct an empirical analysis to explore the determinants of income distribution in terms of macroeconomics. Results - The findings indicate that the income distribution is related with macroeconomics. More specifically, the export, import, GDP and foreign direct investment play a role in deteriorating the income distribution. Conversely, the industrialization, inflation and employment can improve the income distribution. Unfortunately, the inflation and employment do not get through under 5% significant test. Conclusions - Due to that a good income distribution can be beneficial for both a country and an individual, this paper provides a new scope for China's government to improve its income distribution in terms of macroeconomics.

• Journal of the military operations research society of Korea
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• v.22 no.1
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• pp.114-128
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• 1996

In this paper, a life distribution fitting method based on generalized phase-type distributions(GPH) is presented. By fitting the life distribution to a GPH, we can utilize various useful properties of the GPH. Two different approaches are used according to the properties of the given failure time data. One is an approximation to a GPH through the piecewise Weibull failure rate(PWF) model and the other is a direct approximation to a GPH using the empirical distribution function. Two numerical examples are also presented. In the first example, both of the two approaches are utilized and compared for an incomplete data set. And in the second example, the direct approximation method from an empirical distribution is utilized for the analysis of a complete data set. In both cases, we could confirm the validity of the proposed method.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.261-274
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• 2014

In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.537-550
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• 2006

In this paper, we develope three modified empirical distribution function type tests, the modified Cramer-von Mises test, the modified Anderson-Darling test, and the modified Kolmogorov-Smirnov test for the two-parameter exponential distribution with unknown parameters based on multiply Type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.