• Wind and Structures
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• v.1 no.2
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• pp.145-160
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• 1998

In recent years, the effects of a possible climate change have been discussed in regard to wind loading on buildings and structures. Simple scenarios based on the assumption of global warming suggest an increase of storm intensities and storm frequencies and a possible re-distribution of storm tracks. Among recent publications, some papers seem to verify these scenarios while others deny the influence of climatic change. In an introductory step, the paper tries to re-examine these statements. Based on meteorological observations of a weather station in Germany, the existence of long-term trends and their statistical significance is investigated. The analysis itself is based on a refined model for the wind climate introducing a number of new basic variables. Thus, the numerical values of the design wind loads used in modern codes become more justified from the probabilistic point of view.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.1-16
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• 2002

Since changepoint identification is important in many data analysis problem, we wish to make inference about the locations of one or more changepoints of the sequence. We consider the Bayesian nonparameteric inference for multiple changepoint problem using a Bayesian segmentation procedure proposed by Yang and Kuo (2000). A mixture of products of Dirichlet process is used as a prior distribution. To decide whether there exists a single change or not, our approach depends on nonparametric Bayesian Schwartz information criterion at each step. We discuss how to choose the precision parameter (total mass parameter) in nonparametric setting and show that the discreteness of the Dirichlet process prior can ha17e a large effect on the nonparametric Bayesian Schwartz information criterion and leads to conclusions that are very different results from reasonable parametric model. One example is proposed to show this effect.

• Journal of the Korean earth science society
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• v.32 no.5
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• pp.453-460
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• 2011

By performing a statistical change-point analysis of activities of the tropical cyclones (TCs) that have affected Korea (K-TCs), it was found that there was a significant change between 1983 and 1984. During the period of 1984-2004 (P2), more TCs migrated toward the west, recurved in the southwest, and affected Korea, compared to the period of 1965-1983 (P1). These changes for P2 were related to the southwestward expansion of the subtropical western North Pacific high (SWNPH) and simultaneously elongation of its elliptical shape toward Korea. Because of these changes, the central pressure and lifetime of K-TC during P2 were deeper and longer, respectively, than figures for P1. This stronger K-TC intensity for P2 was related to the more southwestward genesis due to the southwestward expansion of the SWNPH. The weaker vertical wind shear environment during P2 was more favorable for K-TC to maintain a strong intensity in the mid-latitudes of East Asia.

• Journal of Korea Water Resources Association
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• v.43 no.7
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• pp.645-655
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• 2010

In this study, occurrences of relative probabilistic changing points between Chukwooki rainfall data (CWK) and modern rain gage data (MRG) were analyzed using Barry and Hartigan (BH) Bayesian changing points estimation method which estimated the changing points by calculation of change probabilities at each point. Since any natural phenomenon cannot be simulated identically and perfectly, a statistical method which can not consider the sequential order has its limitation on prediction of a specific time of occurrence. In this respect, Homogeneity analysis between CWK and MRG was performed through the occurrence investigation of relative probabilistic changing points for four rainfall characteristics of data sets using BH bayesian model which estimate the change point by calculating the relative probabilities in each data points. The results show that statistical characteristics of CWK are not different significantly from MRG, even though considered that there may be little quantitative difference CWK and MRG caused from limitation of measurement accuracy of CWK.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.245-255
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• 2011

There are two nonparametric methods that use empirical distribution functions and probability density estimators for the test of the distribution change of data. In this paper we investigate the two methods precisely and summarize the results of previous research. We assume several probability models to make a simulation study of the change point analysis and to examine the finite sample behavior of the two methods. Empirical powers are compared to verify which is better for each model.

• Journal of the Korean earth science society
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• v.33 no.1
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• pp.49-58
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• 2012

Through a statistical change-point analysis, this study found that Korea landfalling tropical cyclone (TC) frequency has increased rapidly since 1981. This increase is due to the following phenomenon. When anomalous cyclone is developed in the East Asian continent, anomalous anticyclone is reinforced in the western Pacific, which is related to the eastward shift of western North Pacific high, and thus anomalous southerly is formed to Korea from low-latitudes. This anomalous southerly plays an important role as steering flow in moving TCs toward Korea. To examine the cause of the development of anomalous cyclone in the East Asian continent, this study analyzed the water equivalent of accumulated snow depth during the preceding spring (March to May). As a result, less snow depth is observed in most regions of the East Asian continent than before 1981. Therefore, anomalous cyclone in the East Asian continent in summer can be reinforced by the land heating from the preceding spring and then the steering flow of anomalous southerly that moves TCs toward Korea can be also developed to Korea from low-latitudes in summer.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.439-447
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• 2021

Due to the frequent emergence of global abnormal climates, related studies on meteorological change is being actively proceed. However, the research on trend analysis using weather data accumulated over a long period of time was insufficient. In this study, the trend of temperature time series data accumulated from automated surface observing system (ASOS) for 40 years was analyzed by using a non-parametric analysis method. As a result of the Mann-Kendall test on the annual average temperature and seasonal average temperature time series data in South Korea, it has shown that an upward trend exists. In addition, the result of calculating the Sen's slope, which can determine the degree of tendency before and after the searched change point by applying the Pettitt test, recent data after the fluctuation point confirmed that the tendency of temperature rise was even greater.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.753-766
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• 2014

The future mean sea level rise (MSLR) due to climate change in major harbors of Korean Peninsula has been estimated by some statistical methods in this article. Firstly, Mann-Kendall non-parametric trend test to find some trend in the observed long-term tidal data has been performed and also Bayesian change point analysis has been used also to detect the location of change points and their magnitude quantitatively. Especially, in this study, the results from Bayesian change point analysis have been applied to combine 4 future MSLR scenario projections with local MSLR data at 5 tidal gauges. This proposed procedure including Bayesian change point analysis results can improve the step for the determination of starting years of future MLSR scenario projections with 18.6-year lunar node tidal cycle and effectively consider local characteristics at each gauge. The final results by the proposed procedure in this study have shown that the future MSLR in Jeju region (Jeju tidal gauge) is in the largest increment and also the future MSLRs in Western region (Boryeong tidal gauge) and Southern region (Busan tidal gauge) are in the second largest one. Finally, it has been shown that the future MSLRs in Southern region (Yeosu tidal gauge) and Eastern region (Sokcho tidal gauge) seem to be in the relatively smallest growth among 5 gauges.

• Korean Journal of Environmental Agriculture
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• v.38 no.3
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• pp.133-138
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• 2019

BACKGROUND: Production function gives the equation that shows the relationship between the quantities of productive factors used and the amount of product obtained, and can answer a variety of questions. This study was carried out to evaluate the relationship between irrigation water used for rice production and rice productivity by the production function which shows the mathematical relation between input and output. METHODS AND RESULTS: The statistical data on rice production and on the amount of irrigation water were used for the production function analysis. The analysis period was separated for 1966-1981 and 1982-2011, based on goal's change on agriculture from 'increasing food' to 'complex farming'. The relation between irrigation and yield considering production function is a short-term production function both before and after 1982. These results can be expressed by the sigmoid relation. When comparing the graphs of the two analyzed periods, there are differences in quantity between the maximum point and the minimum point during the same analysis period, which can be called an 'Irrigation Effect' by the difference of irrigation, and 'Technical Effect' by the difference by inputs like as fertilizers etc. CONCLUSION: The results could be useful as information for assessing the relationship between agricultural water and the productivity of rice and predicting rice productivity by irrigation water in Korea.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.87-100
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• 2003

Most of statistical data are generated by a set of dynamic, stochastic, and simultaneous relations. An important question is how to specify statistical models so that they are consistent with the dynamic feature of those data. A general hypothesis is that the lagged effect of a change in an explanatory variable is not felt all at once at a single point in time, but The impact is distributed over a number of future points in time. In other words, current control variables are determined by a function that can be reduced to a distributed lag function of past observations. It is possible to explain the relationship between variables in different points of time and to estimate the long-run impacts of a change in a variable on another if time lag series of explanatory variables are incorporated in the model specification. In this study, distributed lag structure is applied to the domestic stock market model to capture the dynamic response of the market by exogenous shocks. The Domestic market is found more responsive to the changes in foreign market factors both in the short and the long run.