• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.889-904
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• 2021

This study is a follow-up study of Kang and Kim (2020). In this study, we derive the sample influence functions of the t-statistic which were not directly derived in previous researches. Throughout these results, we both mathematically examine the relationship between the empirical influence function and the sample influence function, and consider a method to approximate the sample influence function by the empirical influence function. Also, the validity of the relationship between an approximated sample influence function and the empirical influence function is verified by a simulation of a random sample of size 300 from normal distribution. As a result of the simulation, the relationship between the sample influence function which is derived from the t-statistic and the empirical influence function, and the method of approximating the sample influence function through the empirical influence function were verified. This research has significance in proposing both a method which reduces errors in approximation of the empirical influence function and an effective and practical method that evolves from previous research which approximates the sample influence function directly through the empirical influence function by constant revision.

• International Journal of Reliability and Applications
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• v.14 no.2
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• pp.107-114
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• 2013

Modelling of failures is an important element of reliability modelling. Empirical modelling approach suitable for complex item is explored in this paper. First step of the empirical modelling approach is to plot hazard function, density function, Weibull probability plot as well as cumulative intensity function to see which model fits best for the given data. Next step of the empirical modelling approach is select appropriate model for the data and fit the parametric model accordingly and estimate the parameters.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.527-540
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• 2020

While analyzing data, researching outliers, which are out of the main tendency, is as important as researching data that follow the general tendency. In this study we discuss the influence function for outlier discrimination. We derive sample influence functions of sample mean, sample variance, and sample standard deviation, which were not directly derived in previous research. The results enable us to mathematically examine the relationship between the empirical influence function and sample influence function. We can also consider a method to approximate the sample influence function by the empirical influence function. Also, the validity of the relationship between the approximated sample influence function and the empirical influence function is also verified by the simulation of random sampled data in normal distribution. As the result of a simulation, both the relationship between the two influence functions, sample and empirical, and the method of approximating the sample influence function through the emperical influence function were verified. This research has significance in proposing a method that reduces errors in the approximation of the empirical influence function and in proposing an effective and practical method that proceeds from previous research that approximates the sample influence function directly through empirical influence function by constant revision.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.49-56
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• 2001

In this paper we consider empirical Bayes estimation of the hazard rate and survival probabilities with right censored data under the assumption that the hazard function is constant over the period of observation and the prior distribution is gamma. We provide an estimator of the first derivative of the prior moment generating function that converges at each point to the true value in $L_2$ and use it to obtain, easy to compute, asymptotically optimal estimators under the squared error loss function.

• Fire Science and Engineering
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• v.16 no.3
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• pp.16-25
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• 2002

For Freon-23, a conventional extinguished agent regulated by Montreal Protocol and HFC-227ea, its alternative, the empirical equations were correlated in terms of saturated pressure, density, viscosity, enthalpy and surface tension. They were obtained by regression analysis from the experimental data in the literature. The empirical equations of saturated pressure were expressed as the second and third order function of temperature. The empirical equation of density was expressed as compressibility factor and saturated pressure by a function of temperature. The empirical equation of viscosity was formulated as a power function. Heat capacities as well as enthalpies were well fitted by empirical form of the second-order temperature. Finally, surface tension simply has linear function form in terms of temperature.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.353-365
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• 2004

In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

• Fire Science and Engineering
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• v.17 no.1
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• pp.26-32
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• 2003

Inert gases, Af, $N_2$, $CO_2$, as a Halon alternative, the empirical equations were correlated in terms of saturated pressure, density and viscosity, They were obtained by regression analysis from the experimental data in the literature. The empirical equations of saturated pressure were expressed as the second and third order function of temperature. The empirical equation for Ar and $N_2$ of density were expressed as the first order function of temperature. And $CO_2$ was expressed as the second and third order function of temperature. The empirical equation of viscosity was formulated as a power function with temperature. This empirical equations would allow us to predict pure component state.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.2
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• pp.59-65
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• 2020

The empirical Green's function method is applied to the foreshock and the mainshock of the 2016 Gyeongju earthquake to simulate strong ground motions of the mainshock and scenario earthquake at seismic stations of seven metropolises in South Korea, respectively. To identify the applicability of the method in advance, the mainshock is simulated, assuming the foreshock as the empirical Green's function. As a result of the simulation, the overall shape, the amplitude of PGA, and the duration and response spectra of the simulated seismic waveforms are similar with those of the observed seismic waveforms. Based on this result, a scenario earthquake on the causative fault of Gyeongju earthquake with a moment magnitude 6.5 is simulated, assuming that the mainshock serves as the empirical Green's function. As a result, the amplitude of PGA and the duration of simulated seismic waveforms are significantly increased and extended, and the spectral amplitude of the low frequency band is relatively increased compared with that of the high frequency band. If the empirical Green's function method is applied to several recent well-recorded moderate earthquakes, the simulated seismic waveforms can be used as not only input data for developing ground motion prediction equations, but also input data for creating the design response spectra of major facilities in South Korea.

• Korean Journal of Child Studies
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• v.38 no.2
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• pp.17-35
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• 2017

Objective: The purpose of this study was to explore research trends in childhood executive function in Korean academic journal articles. This study showed which population groups were studied, which factors of executive function were measured, and which domains were studied in the selected articels. Methods: A systematic review of empirical studies of childhood executive function published in Korean academic journals from 2006 to 2016 was conducted. Through searching the KERIS database, 60 empirical studies were selected for review. Results: The results of the analyses showed that the population group the most studied was normal young children and that factors of executive function most studied were inhibition, cognitive flexibility, and working memory. Conclusion: Based on this systematic review of empirical studies of childhood executive function, several suggestions for future research are addressed.