• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.159-171
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• 2001

Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent ; that is, the power of the test will not approach 1 as the sample size increases. Hence we give a test based on the ratio of two asymptotically efficient estimates of scale. We also have conducted a power study to compare the test procedures, using Monte Carlo samples from a wide range of alternatives. It is found that the suggested statistics have higher power for the alternatives with the coefficient of variation greater that or equal to 1.

• KDI Journal of Economic Policy
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• v.40 no.1
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• pp.67-83
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• 2018

We have hypothesized that nuclear risk is significantly inversely related to the distance from residences to nuclear power plants and that the level of life satisfaction of residents therefore increases with the distance. We empirically explore the relationship between Ulsan citizens' life satisfaction levels and the distance between their residences and the Kori and Wolsong nuclear power plants (NPP) based on the life satisfaction approach (LSA). The dataset we used covers only Ulsan citizens from the biennial Ulsan Statistics on Citizen's Living Condition and Consciousness of 2014 and 2016. Controlling for micro-variables such as education, work satisfaction, gender, marital status, and expenditures, we found a statistically significant relationship between life satisfaction and the distance between the residences and the nuclear power plants. Nuclear negative externalities including (i) health and environmental impact, (ii) radioactive waste disposal, and (iii) the effect of severe accidents can be quantified in terms of LS units and monetary units. We were able to calculate the monetary value of NPP externalities at $277 per kilometer of distance for Kori and $280 per kilometer of distance for Wolsong at constant 2015 prices. These estimates are quite different from the traditional estimates made with the contingent valuation method, whereas they are similar to the findings of LSA studies abroad. Hence, the need to adopt the LSA in South Korea and policy implications are demonstrated.

• Journal of Environmental Science International
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• v.27 no.6
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• pp.425-436
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• 2018

To establish initial response scenarios for nuclear accidents around the Kori nuclear power plants, the potential for radionuclide diffusion was estimated using numerical experiments and statistical techniques. This study used the numerical model WRF (Weather Research and Forecasting) and FLEXPART (Flexible Particle dispersion model) to calculate the three-dimensional wind field and radionuclide dispersion, respectively. The wind patterns observed at Gijang, near the plants, and at meteorological sites in Busan, were reproduced and applied to estimates of seasonally averaged wind fields. The distribution of emitted radionuclides are strongly associated with characteristics of topography and synoptic wind patterns over nuclear power plants. Since the terrain around the power plants is complex, estimates of radionuclide distribution often produce unexpected results when wind data from different sites are used in statistical calculations. It is highly probable that in the summer and autumn, radionuclides move south-west, towards the downtown metropolitan area. This study has clear limitations in that it uses the seasonal wind field rather than the daily wind field.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.563-571
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• 2001

In this paper, we study selecting a transformation so that the transformed variable is nearly symmetrically distributed. The large sample properties of an M-estimator of transformation parameter that is obtained by minimizing the integrated square of the imaginary part of the empirical characteristic function are investigated when a random sample is selected from some unspecified distribution. According to influence function calculations and Monte Carlo simulations, these estimates are less sensitive, than the normal model maximum likelihood estimates, to a few outliers.

• Communications of the Korean Mathematical Society
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• v.28 no.4
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• pp.751-766
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• 2013

We study the existence and long-time behavior of solutions to the following semilinear degenerate parabolic equation on $\mathbb{R}^N$: $$\frac{{\partial}u}{{\partial}t}-div({\sigma}(x){\nabla}u+{\lambda}u+f(u)=g(x)$$, under a new condition concerning a variable non-negative diffusivity ${\sigma}({\cdot})$. Some essential difficulty caused by the lack of compactness of Sobolev embeddings is overcome here by exploiting the tail-estimates method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.454-457
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• 1997

As in most industrial processes, the dynamic characteristics of an electric power system are subject to changes. Amongst those effects which cause the system to be uncertain, faults on transmission lines are considered. For the stabilization of the power system, we present an indirect adaptive control method, which is capable of tracking a sudden change in the effective reactance of a transmission line. As the plant dynamics are nonlinear, an input-output feedback linearization method equipped with nonlinear damping terms is combined with an identification algorithm which estimates the effect of a fault. The stability of the resulting adaptive nonlinear system is investigated.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1221-1224
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• 1996

As in most industrial processes, the dynamic characteristics of an electric power system are subject to changes. Amongst those effects which cause the system to be uncertain, faults on transmission lines are considered. For the stabilization of the power system, we present an indirect adaptive control method, which is capable of tracking a sudden change in the effective reactance of a transmission line. As the plant dynamics are nonlinear, an input-output feedback linearization method is combined with an identification algorithm which estimates the effect of a fault.

• Journal of Biomedical Engineering Research
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• v.13 no.2
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• pp.125-132
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• 1992

Background EEG signals can be represented as the sum of a conventional AR process and an innovation process. It Is know that conventional estimation techniques, such as least square estimates (LSE) or Gaussian maximum likelihood estimates (MLE-G ) are optimal when the innovation process satisfies the Gaussian or presumed distribution. When the data are contaminated by outliers, however, these assumptions are not met and the power spectrum estimated by conventional estimation techniques may be fatally biased. EEG signal may be affected by artifacts, which are outliers in the statistical term. So the robust filtering estimation technique is used against those artifacts and it performs well for the contaminated EEG signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1501-1509
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• 1996

Mobile stations can be classified by the transmission power level in CDMA system. Different performance parameters will be given to each class of mobile stations so that the appropriate quality ofservices can be provided. In this paper, it is assumed that there are two clsses of mobile stations. with the classification of mobile stations, analytical models are presented for the estimates of the reverse link capacity and the blocking probability. From the model for the reverse link capacity, the maximum number of each class of mobile stations to be served is derived. It is shown that $E_{b/}$I reduction of 1 dB allows the capacity to be increased by 25% and the data transmission rate and the power control accuracy have a significant effect on the reverse link capacity and the blocking probability. Simulation results are provided for validating the anlaytical estimates of the blocking probability.ocking probability.y.