• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.239-254
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• 2021

This paper studies time series analysis with estimation and forecasting for Korean COVID-19 confirmed cases, based on the approach of a heterogeneous autoregressive (HAR) model with two-piece t (TP-T) distributed errors. We consider HAR-TP-T time series models and suggest a step-by-step method to estimate HAR coefficients as well as TP-T distribution parameters. In our proposed step-by-step estimation, the ordinary least squares method is utilized to estimate the HAR coefficients while the maximum likelihood estimation (MLE) method is adopted to estimate the TP-T error parameters. A simulation study on the step-by-step method is conducted and it shows a good performance. For the empirical analysis on the Korean COVID-19 confirmed cases, estimates in the HAR-TP-T models of order p = 2, 3, 4 are computed along with a couple of selected lags, which include the optimal lags chosen by minimizing the mean squares errors of the models. The estimation results by our proposed method and the solely MLE are compared with some criteria rules. Our proposed step-by-step method outperforms the MLE in two aspects: mean squares error of the HAR model and mean squares difference between the TP-T residuals and their densities. Moreover, forecasting for the Korean COVID-19 confirmed cases is discussed with the optimally selected HAR-TP-T model. Mean absolute percentage error of one-step ahead out-of-sample forecasts is evaluated as 0.0953% in the proposed model. We conclude that our proposed HAR-TP-T time series model with optimally selected lags and its step-by-step estimation provide an accurate forecasting performance for the Korean COVID-19 confirmed cases.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.201-210
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• 2008

The government employment statistics show the close comovement of the whole domestic unemployment rate with the youth unemployment rate for the past 10 years, implying the dominant influence of the unemployment of the youth age. This study investigates the structure of the short-run variation and the process of the long-run adjustment in the unemployment rates of the youth and middle ages by formulating the dynamic equation system. The estimation result consistently reflects the vulnerability of the youth class in the aggravation of the employment condition. The effect of exogenous changes is found to be persistent in the unemployment rates of both ages, which appear to have similar structures of the long-run time path. However, the youth unemployment rate turns out to have a relatively long adjustment process to the long-run equilibrium.

• Convergence Security Journal
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• v.17 no.3
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• pp.95-101
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• 2017

Reliability is the priority matter in guided weapon systems. The reliability prediction data is used during the devel opment stage as the manufacturing cost is very high and the production quantity if quite limited. At the same time it takes relatively a long period of time to acquire a reliable operation data set after deployment such that in order t o determine the operational reliability, weapons must be tested and analyzed in real operating environments. For the research, the life distributions were estimated by using actual operation data and the reliability was calculated by ap plying the method of least squares and maximum likelihood estimation. Also, the comparisons were made between pr edicted reliability and actual operational reliability. As a result, the actual reliability of each system was higher than predicted reliability and it was considered that such a difference was caused by the fact that the application of the l atest designing technology and improved parts to the guided weapon systems was not reflected on the estimation of predicted reliability. It was possible to confirm the actual operational reliability of domestic (ROK) guided weapon sy stems through this research and the methods used here will contribute to the reliability analyses for the future guide d weapon systems to be developed.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1553-1567
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• 1996

The numerous applications surface interpolation include the modeling and visualization phenomena. A tetrahedrization is one of pre-processing steps for 4-D space interpolation. The quality of a piecewise linear interpolation 4-D space depends not only on the distribution of the data points in $R^2$, but also on the data values. We show that the quality of approximation can be improved by data dependent tetraheadrization through visualization of 4-D space. This paper discusses Delaunary tetrahedrization method(sphere criterion) and one of the data dependent tetrahedrization methods(least squares fitting criterion). This paper also discusses new data dependent criteria:1) gradient difference, and 2) jump in normal direction derivative.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.10 no.1
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• pp.1-11
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• 2012

The equation of the step-drawdown test "$s_w=BQ+CQ^p$" written by Rorabaugh (1953) is suitable for drawdown increased non-linearly in the fractured rocks. It was found that value of root mean square error (RMSE) between observed and calculated drawdowns was very low. The calculated $C$ (well head loss coefficient) and $P$ (well head loss exponent) value of well head losses ($CQ^p$) ranged $3.689{\times}10^{-19}{\sim}5.825{\times}10^{-7}$ and 3.459~8.290, respectively. It appeared that the deeper depth in pumping well the larger drawdowns due to pumping rate increase. The well head loss in the fractured rocks, unlike that in porous media, is affected by properties of fractures (fractures of aperture, spacing, and connection) around pumping well. The $C$ and $P$ value in the well head loss is very important to interpret turbulence interval and properties of high or low permeability of fractured rock. As a result, regression analysis of $C$ and $P$ value in the well head losses identified the relationship of turbulence interval and hydraulic properties. The relationship between $C$ and $P$ value turned out very useful to interpret hydraulic properties of the fractured rocks.

• Korean Journal of Social Welfare Studies
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• v.47 no.4
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• pp.217-254
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• 2016

The purpose of this study is comparing fiscal sustainability of 17 welfare states. Borrowed the concept of fiscal space to Ostry et al(2010) and Ghosh et al(2011), this study measures the fiscal sustainability in welfare states. Using data collected from 20 OECD countries from 1986 to 2013, this study attempts to evaluate the financial sustainability of each country. As a result, it is necessary that the appropriate level of tax burden is secured. Tax revenue is the funded basis for maintaining the welfare state, so increasing tax compliance to offset the negative impact of increasing welfare spending will promote social cohesion. In therms of tax structure, in accordance with the ability to pay principle, it is important to raise the equity between the source of taxation. Reducing the gap between labor and capital tax is required to achieve horizontal equity, It is also useful to utilize the financial base of the welfare state by broadening the tax base though a consumption tax. Improving the vertical equity can also make a positive contribution to the fiscal sustainability of the welfare state.

• Journal of the Korean Regional Science Association
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• v.40 no.1
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• pp.3-17
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• 2024

Despite extensive discussions on the repercussions of the prolonged COVID-19 pandemic, there is a lack of analysis on the relationships and changes in relationships between business districts Therefore, this study aims to understand the impact of COVID-19 on retail business districts in Seoul by considering the geographical dependency and interactions of these districts. Using data from the fourth quarters of 2019 to 2021 for 1,490 retail business districts in Seoul, we employed the 3-Stage Least Squares (3SLS) estimation method for simultaneous equation modeling to empirically examine how spatial dependencies among retail business districts in Seoul have evolved due to the influence of COVID-19. The results indicate the existence of spatial dependence among retail business districts in Seoul, with developmental districts exerting a negative influence on nearby districts. Furthermore, the analysis reveals changes in dependency patterns after the onset of COVID-19, interpreted as a decrease in commercial activities in developmental districts due to the impact of the pandemic. The significance of this study lies in providing new insights into Seoul's retail business districts through a spatially dependent analysis, offering a foundation for various stakeholders, including government, local authorities, and small business owners, to respond appropriately to changes in business districts by considering their interrelationships.