• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.531-550
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• 2023

The estimation of extreme quantiles is one of the main objectives of statistics of extremes (which deals with the estimation of rare events). In this paper, a robust estimator of extreme quantile of a heavy-tailed distribution is considered. The estimator is obtained through the minimum density power divergence criterion on an exponential regression model. The proposed estimator was compared with two estimators of extreme quantiles in the literature in a simulation study. The results show that the proposed estimator is stable to the choice of the number of top order statistics and show lesser bias and mean square error compared to the existing extreme quantile estimators. Practical application of the proposed estimator is illustrated with data from the pedochemical and insurance industries.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.1
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• pp.9-14
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• 2022

Social infrastructure facilities such as production, transportation, gas and electricity facilities may experience poor performance depending on time, load, temperature, etc. and may require maintenance, repair and management as they are used. In particular, in the case of transformers, the process of managing them for the purpose of preventing them from failing is necessary because a failure can cause enormous social damage. The management of transformers should consider both technical and economic aspects and strategic aspects at the same time. Thus, it applies the Asset Management concept, which is widely used in the financial industry as an advanced method of transformer management techniques worldwide. In this paper, the operation and power outage data were secured for the asset management of the transformer for distribution, and the asset status was analyzed. Analysis of asset status using actual operation and power outage data is essential for assessing the statistical life and failure rate of the facility. Through this paper, the status of transformer assets for arbitrary A group distribution was analyzed, and the end of life and replacement life were calculated.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.417-429
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• 1998

This paper compares powers of the two nonparametric tests under a variety of population distributions through a simulation study. Both tests require that the two underlying populations have the same variance, but this assumption is relaxed in some of the comparisons.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.537-546
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• 2012

In this paper, for analyzing binary data, Poisson regression with offset and logistic regression are compared with respect to the power via simulations. Poisson distribution can be used as an approximation of binomial distribution when n is large and p is small; however, we investigate if the same conditions can be held for the power of significant tests between logistic regression and offset poisson regression. The result is that when offset size is large for rare events offset poisson regression has a similar power to logistic regression, but it has an acceptable power even with a moderate prevalence rate. However, with a small offset size (< 10), offset poisson regression should be used with caution for rare events or common events. These results would be good guidelines for users who want to use offset poisson regression models for binary data.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.13-26
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• 2008

Inference on the present data will be more reliable when the data arising from previous similar studies are available. The data arising from previous studies are referred as historical data. The power prior is defined by the likelihood function based on the historical data to the power $a_0$, where $0\;{\le}\;a_0\;{\le}\;1$. The power prior is a useful informative prior for Bayesian inference such as model selection and model comparison. We utilize the historical data to perform multiple comparison in the one-way ANOVA model. We demonstrate our results with some simulated datasets under a simple order restriction between the treatments.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.993-1002
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• 2008

Correlated responses have been widely analyzed since Liang and Zeger (1986) introduced the famous Generalized Estimating Equations(GEE). However, their variance functions were restricted to known quantifies multiplied by scale parameter. In so many industries and academic/research fields, power-of-the-mean variance function is one of the common variance function. We suggest GEE-type pseudolikelihood estimation based on the power-of-the-mean variance using existing software and investigate it's efficiency for different working correlation matrices.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.435-444
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• 2014

The most widely used optimal bandwidth is known to minimize the mean integrated squared error(MISE) of a kernel density estimator from a true density. In this article proposes, we propose a bandwidth which asymptotically minimizes the mean integrated density power divergence(MIDPD) between a true density and a corresponding kernel density estimator. An approximated form of the mean integrated density power divergence is derived and a bandwidth is obtained as a product of minimization based on the approximated form. The resulting bandwidth resembles the optimal bandwidth by Parzen (1962), but it reflects the nature of a model density more than the existing optimal bandwidths. We have one more choice of an optimal bandwidth with a firm theoretical background; in addition, an empirical study we show that the bandwidth from the mean integrated density power divergence can produce a density estimator fitting a sample better than the bandwidth from the mean integrated squared error.

• Journal of the Korean Magnetics Society
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• v.12 no.6
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• pp.224-230
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• 2002

The statistical experiment method is employed to optimize the deposition condition of Co film with DC magnetron sputtering process. The statistical treatment results showed the significance value below 0.05, low RMS error and R-sq value close to 1, which implied that our experiment and design were very reliable. We found that the sheet resistance decreased to -1.83Ω/$\square$ with the deposition temperature, increased to 11.17Ω/$\square$ with the deposition pressure, and decreased into -0.65Ω/$\square$ with the DC power. We also confirmed that the sheet resistance uniformity was mainly influenced by the deposition temperature as it decreased -4.04％ at the temperature range of 25$\^{C}$∼147$\^{C}$. Finally, we report that the optimum condition of Co film using our statistical method of design of experiment is the deposition temperature of 25$\^{C}$, the deposition pressure of 12mTorr, and the DC power of 1500W.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.27-37
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• 2011

dth-order power analysis can safely be defended by dth-order masking method. However, as the degree of applied masking method increases, it can significantly decrease effectiveness of cryptosystem. The existing statistical analysis on high-order power analysis contains only analysis on second power analysis. However, this means absent of safety standards when crypto engineers apply 3rd or more order masking. this absent of standards can lead to insignificant usage of masking method which can significantly decrease effectiveness of cryptosystem. In this dissertation, we have generalize statistical values on high-order power analysis to establish these standards. In other words, we have generalized the value of a correlation coefficient when calculation of high-order power analysis methods are performed. That is to say, it can greatly be used to indicate a degrees that can be applied on further usage of masking method.

• Nuclear Engineering and Technology
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• v.35 no.5
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• pp.387-398
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• 2003

For reference human intrusion scenarios constructed in previous study, a probabilistic safety assessment to derive the radionuclide concentration limits for the low- and intermediate- level radioactive waste disposal facility is conducted. Statistical approach by the Latin Hypercube Sampling method is introduced and new assumptions about the disposal facility system are examined and discussed. In our previous study of deterministic approach, the post construction scenarios appeared as most limiting scenario to derive the radionuclide concentration limits. Whereas, in this statistical approach, the post drilling and the post construction scenarios are mutually competing for the scenario selection according to which radionuclides are more important in safety assessment context. Introduction of new assumption shows that the post drilling scenario can play an important role as the limiting scenario instead of the post-construction scenario. When we compare the concentration limits between the previous and this study, concentrations of radionuclides such as Nb-94, Cs-137 and alpha-emitting radionuclides show elevated values than the case of the previous study. Remaining radionuclides such as Sr-90, Tc-99 I-129, Ni-59 and Ni-63 show lower values than the case of the previous study.