• Journal of Korea Water Resources Association
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• v.52 no.2
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• pp.141-148
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• 2019

When simulating the daily rainfall amount by existing Markov Chain model, it is general to simulate the rainfall occurrence and to estimate the rainfall amount randomly from the distribution which is similar to the daily rainfall distribution characteristic using Monte Carlo simulation. At this time, there is a limitation that the characteristics of rainfall intensity and distribution by time according to the rainfall duration are not reflected in the results. In this study, 1-day, 2-day, 3-day, 4-day rainfall event are classified, and the rainfall amount is estimated by rainfall duration. In other words, the distributions of the total amount of rainfall event by the duration are set using the Kernel Density Estimation (KDE), the daily rainfall in each day are estimated from the distribution of each duration. Total rainfall amount determined for each event are divided into each daily rainfall considering the type of daily distribution of the rainfall event which has most similar rainfall amount of the observed rainfall using the k-Nearest Neighbor algorithm (KNN). This study is to develop the limitation of the existing rainfall estimation method, and it is expected that this results can use for the future rainfall estimation and as the primary data in water resource design.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.81-93
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• 2015

Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.32-36
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• 2011

가뭄은 홍수와 같이 단기간에 피해를 발생시키는 것이 아니라 장기간에 걸쳐 서서히 진행되므로 그 심각성을 인식하기 어렵고 국가 차원의 대책 또한 미비한 실정이다. 따라서 본 연구에서는 가뭄의 발생특성을 파악하기 위해 기상학적 가뭄지수를 산정하여 가뭄빈도해석을 실시하였다. 빈도해석방법은 weibull분포를 이용한 매개변수적 방법과 경계핵밀도함수(Boundary Kernel Density Function)를 이용한 비매개변수적 방법을 병행하여 재현기간별 가뭄심도를 산정하였다.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.347-349
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• 1995

In this paper a central limit theorem on $L^P(R)$ for $1{\leq}p<{\infty}$ is obtained with an example when ${X_n}$ is a sequence of independent, identically distributed random variables on $L^P(R)$.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.141-149
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• 2013

We present methods for studying the log-density ratio that enables the selection of the predictors and the form to be included in the logistic regression model. Under bivariate normal distributional assumptions, we investigate the form of the log-density ratio as a function of two predictors. If two covariance matrices are equal, then the crossproduct and quadratic terms are not needed. If the variables are uncorrelated, we do not need the crossproduct terms, but we still need the linear and quadratic terms. We also explore other conditions in which the crossproduct and quadratic terms are not needed in the logistic regression model.

• East Asian Economic Review
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• v.27 no.1
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• pp.33-60
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• 2023

This paper analyzes the entire distribution of stock market returns/volatility in five emerging markets (ASEAN5) and figures out the conditional distribution of the CHI_EPU index. The aim is to examine the impact of CHI_EPU on the stock returns/volatility density of ASEAN5 markets. It also examined whether changes in CHI_EPU explain returns at higher or lower points (abnormal returns). This paper models the behaviour of stock returns from March 2011 to June 2018 using a non-parametric conditional density estimation approach. The results indicate that CHI_EPU diminishes stock returns and augments volatility in ASEAN5 markets, except for Malaysia, where it affects stock returns positively. The possible reason for this positive impact is that EPU is not the leading factor reducing Malaysian stock returns; but, other forces, such as dependency on other countries' stock markets and global factors, may have a positive impact on stock returns (Bachmann and Bayer, 2013). Thus, the risk of simultaneous investment in Chinese and ASEAN5 stock markets, except Malaysia, is high. Further, the degree of this influence intensifies at extreme high/low intervals (positive/negative tails). The findings of this study have significant implications for investors, policymakers, market agents, and analysts of ASEAN5.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.3
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• pp.191-197
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• 2012

One-class classification (OCC) is one of the recent growing areas in data mining and pattern recognition. In the present study we examine a k-nearest neighbors data description (kNNDD) algorithm, one of the OCC algorithms widely used. In particular, we propose to use nonparametric estimation methods to determine the threshold of the kNNDD algorithm. A simulation study has been conducted to explore the characteristics of the proposed approach and compare it with the existing approach that determines the threshold. The results demonstrate the usefulness and flexibility of the proposed approach.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.127-133
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• 1990

In this article, several problems inherent in histogram estimate of unknown probability density function are discussed. Those include so called sharp comers and bin edge effect. A resolution for these problems occurred with histogram is discussed. The resulting estimate is called kernel density estimate which is most widely used by data analysts. One of the most recent and reliable data-based choices of scale factor (bandwidth) of the estimate, which has been known to be most crucial, is also discussed.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.271-282
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• 1996

this paper deal with the estimation of the power spectral density function of time series. A kernel estimator which is based on local average is defined and the rates of convergence of the pointwise, $$L_2$-norm; and; $L{\infty}$-norm associated with the estimator are investigated by restricting as to kernels with suitable assumptions. Under appropriate regularity conditions, it is shown that the optimal rate of convergence for 0$N^{-r}$ both in the pointwiseand $$L_2$-norm, while; $N^{r-1}(logN)^{-r}$is the optimal rate in the $L{\infty}-norm$. Some examples are given to illustrate the application of main results.

• Structural Engineering and Mechanics
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• v.27 no.5
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• pp.609-623
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• 2007

The problem of a semi-infinite magneto-electro-elastically impermeable mode-III crack in a magneto-electro-elastic material is considered under the action of impact loads. For the case when a pair of concentrated anti-plane shear impacts, electric displacement and magnetic induction impacts are exerted symmetrically on the upper and lower surfaces of the crack, the magneto-electro-elastic field ahead of the crack tip is determined in explicit form. The dynamic intensity factors and dynamic energy density factor are obtained. The method adopted is to reduce the mixed initial-boundary value problem, by using the Laplace and Fourier transforms, into three simultaneous dual integral equations, one of which is converted into an Abel's integral equation and the others into a singular integral equation with Cauchy kernel. Based on the obtained fundamental solutions of point impact loads, the solutions of two kinds of different loading cases are evaluated by integration. For some particular cases, the present results reduce to the previous results.