• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.145-156
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• 2005

In this paper, we derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter of the half-logistic distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.97-103
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• 1995

In this paper, we propose estimators of Gini index of the exponential distribution. We also obtain the distribution and the moments of the proposed estimators. The moments of the proposed estimators are derived by special function. We compare the maximum likelihood estimator (MLE) of Gini index with the proposed estimator of Gini index in the sense of MSE through Monte Carlo Method.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.71-76
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• 1998

By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) of the location parameter and the scale parameter of the two-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1217-1222
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• 2011

In this paper, we show that any circular density can be closely approximated by an exponential family of distributions. Therefore we propose an exponential family of distributions as a new family of circular distributions, which is absolutely suitable to model any shape of circular distributions. In this family of circular distributions, the trigonometric moments are found to be the uniformly minimum variance unbiased estimators (UMVUEs) of the parameters of distribution. Simulation result and goodness of fit test using an asymmetric real data set show usefulness of the novel circular distribution.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1251-1256
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• 2011

Consider a p-variate ($p{\geq}4$) normal distribution with mean ${\theta}$ and identity covariance matrix. Using a simple property of noncentral chi square distribution, the generalized Bayes estimators dominating the Lindley estimator under quadratic loss are given based on the methods of Brown, Brewster and Zidek for estimating a normal variance. This result can be extended the cases where covariance matrix is completely unknown or ${\Sigma}={\sigma}^2I$ for an unknown scalar ${\sigma}^2$.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.817-826
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• 2007

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the location parameter in a generalized extreme value distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.643-653
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• 2014

In this paper, we propose some estimators for the extreme value distribution based on the interval method and mid-point approximation method from the progressive Type-I interval censored sample. Because log-likelihood function is a non-linear function, we use a Taylor series expansion to derive approximate likelihood equations. We compare the proposed estimators in terms of the mean squared error by using the Monte Carlo simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.894-897
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• 2006

Spatial distribution of injected electrons and holes is evaluated by using single-junction charge pumping technique in SONOS(Poly-silicon/Oxide/Nitride/Oxide/Silicon) memory cells. Injected electron are limited to length of ONO(Oxide/Nitride/oxide) region in locally ONO stacked cell, while are spread widely along with channel in fully ONO stacked cell. Hot-holes are trapped into the oxide as well as the ONO stack in locally ONO stacked cell.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1019-1026
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• 2012

This paper presents a method for the identification of "edge observations" located on a boundary area constructed by a truncation variable as well as for the identification of outliers and the after fit of multivariate skew $t$-distribution(MST) to asymmetric data. The detection of edge observation is important in data analysis because it provides information on a certain critical area in observation space. The proposed method is applied to an Australian Institute of Sport(AIS) dataset that is well known for asymmetry in data space.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1397-1409
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• 2017

For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods.