• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.581-587
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• 2010

We shall propose several estimators for the scale parameter in a uniform distri-bution with a generalized uniform outlier when the scale parameter is a function of a known exposure level, and obtain expectations and variances for their proposed estima-tors. And we shall compare numerically efficiencies for proposed estimators of changed parameters of the scale in the small sample sizes.

• Journal of the Korean Mathematical Society
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• v.50 no.3
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• pp.607-625
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• 2013

It is well-known that the ordinary single-parameter Wiener space exhibits a reflection principle. In this paper we establish a reflection principle for a generalized one-parameter Wiener space and apply it to the integration of a class of functionals on this space. We also discuss several notions of a reflection principle for the two-parameter Wiener space, and explore whether these actually hold.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.413-423
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• 2005

Consider the problem of estimating the underlying regression function from a set of noisy data which is contaminated by a long tailed error distribution. There exist several robust smoothing techniques and these are turned out to be very useful to reduce the influence of outlying observations. However, no matter what kind of robust smoother we use, we should choose the smoothing parameter and relatively less attention has been made for the robust bandwidth selection method. In this paper, we adopt the idea of robust location parameter estimation technique and propose the robust cross validation score functions.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.59-68
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• 2005

We consider the problem of estimating the scale and shape parameter of the Weibull distribution based on censored samples. we propose the approximate maximum likelihood estimators (AMLEs) of the scale and shape parameters in the Weibull distribution based on Type-II censored samples. We compare the proposed estimators in the sense of mean squared error (MSE).

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.573-584
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• 2007

We define a skew-symmetric Laplace distribution by a symmetric Laplace distribution and evaluate its coefficient of skewness. And we derive an approximate maximum likelihood estimator(AME) and a moment estimator(MME) of a skewed parameter in a skew-symmetric Laplace distribution, and hence compare simulated mean squared errors of those estimators. We compare asymptotic mean squared errors of two defined estimators of reliability in two independent skew-symmetric distributions.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.955-960
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• 2009

As we shall dene an exponentiated complementary power function distribution, we shall consider moments, hazard rate, and inference for parameter in the distribution. And we shall consider an inference of the reliability and distributions for the quotient and the ratio in two independent exponentiated complementary power function random variables.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.923-931
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• 2005

The two parameter generalized exponential distribution was recently introduced by Gupta and Kundu (1999). It is observed that the generalized exponential distribution can be used quite effectively to analyze skewed data set. This paper develops the accelerated life test model using generalized exponential distribution and considers maximum likelihood estimation of parameters under the tampered random variable model. To show the performance of proposed maximum likelihood estimates, some simulation will be performed. Using a real data set, an example will be given.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1449-1454
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• 2013

There are many methods for measuring the difference between two location parameters. In this paper, statistics are proposed in order to estimate the difference of two location parameters. The statistics are designed not using the means, variances, signs and ranks, but with the cumulative distribution functions. Hence these are measured as the differences in the area between two univariate cumulative distribution functions. It is found that the difference in the area between two empirical cumulative distribution functions is the difference of two sample means, and its integral is also the difference of two population means.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.52-57
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• 1996

Detection of arcing high impedance faults has been a perplexing in the power distribution protection. Transient analysis of distribution disturbances for fault discrimination from other normal events is important for a secure protection of the power system. A simple parameter of wave form distortion quantification is used to analyze the behaviors of arcing faults and normal distribution disturbances. Theoretical perspectives of the transients were studied and actual disturbances were examined. From this investigation, a discrimination guideline based on the revised crest factor is developed. The discrimination method has a high potential to enhance the reliability and security for the distribution system protection.

• Journal of Power System Engineering
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• v.21 no.5
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• pp.79-85
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• 2017

Vickers hardness is an important material in the design and reliability is required. Therefore, these values are very important as the basic data for design, manufacture and development, and the identification of quantitative probability distribution characteristics such as mean and dispersion is a very important parameter in design. In this study, Vickers hardness was measured after artificially heat-treated in the temperature range 753K, where chrome depletion near the grain boundary occurred for three kinds of stainless steels, and the Vickers hardness were evaluated. From the results, Vickers hardness increased with increasing heat treatment temperature. In Weibull distribution for Vickers hardness, the dispersion of STS310S at 813K and 873K was small, and the dispersion of STS316L at 753K, 933K and 993K was small. Also, STS347H exhibited the lowest dispersion at 753K in three kinds of stainless steels. The scale parameter increased with increasing heat treatment temperature in three kinds of stainless steels.