• Journal of Wetlands Research
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• v.14 no.3
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• pp.341-352
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• 2012

The purpose of this study is to statistically project future probable rainfall and to quantitatively assess a future flood vulnerability using flood vulnerability model. To project probable rainfall under non-stationarity conditions, the parameters of General Extreme Value (GEV) distribution were estimated using the 1 yr data added to the initial 30 yr base series. We can also fit a linear regression model between time and location parameters after comparing the linear relationships between time and location, scale, and shape parameters, the probable rainfall in 2030 yr was calculated using the location parameters obtained from linear regression equation. The flood vulnerability in 2030 yr was assessed inputted the probable rainfall into flood vulnerability assessment model suggested by Jang and Kim (2009). As the result of analysis, when a 100 yr rainfall frequency occurs in 2030 yr, it was projected that vulnerability will be increased by spatial average 5 % relative to present.

• Journal of Global Scholars of Marketing Science
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• v.16 no.1
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• pp.13-26
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• 2006

In this research, we develope a procedure for detecting a random non-stationarity to the individual's purchasing rate in a stationary NED model. On this purpose, we derive the likelihood ratio statistic for a testing null and alternative hypotheses defined as whether there is no significant structural change in a stationary NED model or any. Where the structural change comes from a random non-stationarity(marketing mix activities or seasonality, for example) to the individual's purchasing rate. We also apply the developed method to a panel data for a frequently purchased good. This research could be a solution to include the non-stationarity in a stationary NED model. We also expect that the developed model could give a signal for an early detection of significant changes in marketing environment, and a mean for a measurement of the effects of marketing mix activities.

• Environmental and Resource Economics Review
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• v.19 no.3
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• pp.571-595
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• 2010

This research applies an panel data stationarity and stochastic convergence test developed by Carrion-i-Silvestre et al. (2005), which has the advantage of considering multiple structural breaks and the presence of cross-section dependence in order to investigate the hypothesis that relative emission $CO_2$ per capita stochastically converge for 11 Asian countries from 1971~2007. We find that relative emission $CO_2$ per capita is stationary after the structural breaks and cross-section dependence are introduced into the model. We also investigate whether Environmental Kuznets Curve (EKC) hypothesis exists in 11 Asian countries. For EKC test, using the panel cointegration tests of Banerjee and Carrion-i-Silvestre (2006) and Westerlund and Edgerton(2007), we find that relative emission $CO_2$ per capita and relative GDP per capita are cointegrated. However EKC hypothesis in 11 Asian countries is not supported.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.81-96
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• 2017

Along with climate change, it is reported that the scale and the frequency of extreme climate events (e.g. heavy rain, typhoon, etc.) show unstable tendency of increase. In case of Korea, also, the frequency of heavy rainfall shows increasing tendency, thus causing natural disaster damage in downtown and agricultural areas by rainfall that exceeds the design criteria of hydraulic structures. In order to minimize natural disaster damage, it is necessary to analyze how extreme precipitation event changes under climate change. Therefore a new design criteria based on non-stationarity frequency analysis is needed to consider a tendency of future extreme precipitation event and to prepare countermeasures to climate change. And a quantitative and objective characteristic analysis could be a key to preparing countermeasures to climate change impact. In this study, non-stationarity frequency analysis was performed and inundation risk indices developed by 4 inundation characteristics (e.g. inundation area, inundation depth, inundation duration, and inundation radius) were assessed. The study results showed that future probable rainfall could exceed the existing design criteria of hydraulic structures (rivers of state: 100yr-200yr, river banks: 50yr-100yr) reaching over 500yr frequency probable rainfall of the past. Inundation characteristics showed higher value in the future compared to the past, especially in sections with tributary stream inflow. Also, the inundation risk indices were estimated as 0.14 for the past period of 1973-2015, and 0.25, 0.29, 1.27 for the future period of 2016-2040, 2041-2070, 2071-2100, respectively. The study findings are expected to be used as a basis to analyze future inundation damage and to establish management solutions for rivers with inundation risks.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.141-146
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• 2007

In this paper, we consider a Box-Cox transformed threshold GARCH(1,1) process and find a sufficient condition under which the process is geometrically ergodic and has the ${\beta}$-mixing property with an exponential decay rate.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.111-127
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• 2007

The logistic distribution is generalized using the Marshall-Olkin scheme and its generalization. Some properties are studied. First order autoregressive time series model with Marshall-Olkin semi-logistic distribution as marginal is developed and studied.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.983-990
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• 2006

In this paper, we study an asymmetric power fractionally integrated GARCH model and find a region on which the process is stationary ergodic and has long memory property.

• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.359-368
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• 2002

Nonparametric kernel regression problem is considered for a stationary dependent sequence ｛(Xi, Yj) 1 j $\geq$ 1 ｝. In particular consistency and rates of convergence are discussed, which gives some useful insight for the effect of dependence for stationary $\alpha$-mixing sequences.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.323-334
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• 2017

We note that the dynamics of realized volatilities (RVs) are near the boundary between stationarity and non-stationarity because RVs have persistent long-memory and are often subject to fairly large outlying values. To forecast realized volatility, we consider a new method that adaptively use models with and without unit root according to the abnormality of observed RV: heterogeneous autoregressive (HAR) model and the Integrated HAR (IHAR) model. The resulting method is called the IHAR-O-HAR method. In an out-of-sample forecast comparison for the realized volatility datasets of the 3 major indexes of the S&P 500, the NASDAQ, and the Nikkei 225, the new IHAR-O-HAR method is shown superior to the existing HAR and IHAR method.

• Wind and Structures
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• v.24 no.1
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• pp.59-78
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• 2017

Non-stationarity and non-Gaussian property are two of the most important characteristics of wind. These two features are studied in this study based on wind speed records measured at different heights from a 325 m high meteorological tower during the synoptic wind storms. By using the time-frequency analysis tools, it is found that after removing the low frequency trend of the longitudinal wind, the retained fluctuating wind speeds remain to be asymmetrically non-Gaussian distributed. Results show that such non-Gaussianity is due to the weak-stationarity of the detrended fluctuating wind speed. The low frequency components of the fluctuating wind speeds mainly contribute to the non-zero skewness, while distribution of the high frequency component is found to have high kurtosis values. By further studying the decomposed wind speed, the mechanisms of the non-Gaussian distribution are examined from the phase, turbulence energy point of view.