• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1177-1190
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• 2009

The traffic operating speed is one of important information to measure a road capacity. When we supply the information of the road of high traffic by using navigation, offering the present traffic information and the forecasted future information are the outstanding functions to serve the more accurate expected times and intervals. In this study, we proposed the traffic speed forecasting model using the accumulated traffic speed data of the road and highway and forecasted the average speed for each the road and high interval and each time interval using Fourier transformation and time series regression model with trigonometrical function. We also propose the proper method of missing data imputation and treatment for the outliers to raise an accuracy of the traffic speed forecasting and the speed grouping method for which data have similar traffic speed pattern to increase an efficiency of analysis.

• Journal of Korea Port Economic Association
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• v.22 no.3
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• pp.79-96
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• 2006

In this paper, using the gravity model, I examined that the port traffic in the port of Pusan have been influenced by GDP of South Korea, GDP of trading countries, an agreement on maritime transport, maritime transport charge and the local economic integration, etc. In view of the policy implication based on the result of analysis by the gravity model, the port traffic and the transshipment in the port of Pusan is positively influenced by GDP of South Korea, GDP of trading countries and countries on the way of main sea route(LINE). But it is negatively influenced by maritime transport charge. Especially, when a maritime transport charge goes up 1 percentage point, it is estimated that a transshipment decreases about 0.586-0.895 percentage point. So, a maritime transport charge was found to have more effect on a transshipment than a port traffic(except transshipment).

• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.95-101
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• 2021

Marine Incidents based on Heinrich's law are very important in preventing accidents. However, marine Incident data are mainly qualitative and are used to prevent similar accidents through case sharing rather than statistical analysis, which can be confirmed in the marine Incident-related data posted in the Korea Maritime Safety Tribunal. Therefore, this study derived quantitative results by analyzing the causes of marine incidents during berthing using various methods of statistical analysis. To this end, data involving marine incidents from various shipping companies were collected and reclassified for easy analysis. The main keywords were derived via primary analysis using text mining. Only meaningful words were selected via verification by an expert group, and time series and cluster analysis were performed to predict marine incidents that may occur during berthing. Although the role of an expert group was still required during the analysis, it was confirmed that quantitative analysis of marine incidents was feasible, and iused to provide cause and accident prevention information.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.1-7
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• 2021

Although the working environment has changed significantly compared to the past, such as the implementation of the five-day work week and the aging of the population, it is not reflected in the current industrial accident index calculation such as frequency rate, severity rate, and safe T-score. In this study, statistical data were used to understand time-series trends such as increase in life expectancy, working age, shortening of working hours, and average age of death by accident. As a result of time series trend analysis of statistical data, life expectancy increased to 83.3 years, and the legal working age was raised to 65 years due to the aging of the population. Also, with the advent of the 5-day work week since 2001, the average annual working hours decreased to 2008.1 hours. It can be confirmed through statistical data that these phenomena are applied to the current working environment due to a complex action, and these environmental changes affect the calculation results of the industrial accident index.

• Convergence Security Journal
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• v.24 no.2
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• pp.151-160
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• 2024

In recent years with high interest rates and inflations, which worsen people's lives, voice phishing crimes also increase along with damage. Voice phishing that becomes more evolved by technology developments causes serious financial and mental damage to victims. This work aims to study time series models for its accurate prediction. ARIMA, SARIMA and SARIMAX models are compared. As exogenous variables, the amount of damages and the numbers of arrests and criminals are adopted. Forecasting performances are evaluated. Prediction intervals are constructed along with empirical coverages, which justify the superiority of the model. Finally, the numbers of voice phishing up to December 2024 are predicted, through which we expect the establishment of future prevention strategies for voice phishing.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.505-512
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• 2016

The paper is concerned with high frequency financial time series. A weighted hybrid volatility is suggested to compute daily volatilities based on high frequency data. Various realized volatility (RV) computations are reviewed and the weights are chosen by minimizing the differences between the hybrid volatility and the realized volatility. A high frequency time series of KOSPI200 index is illustrated via QLIKE and Theil-U statistics.

• The Korean Journal of Financial Management
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• v.14 no.3
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• pp.183-201
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• 1997

본 논문은 우리나라의 주가지수수익률의 변동특성이 카오스를 내재하고 있는지 아니면 랜덤과정을 따르는지를 분석하기 위하여 Hurst의 R/S분석을 중심으로 분석하였다. 우리나라 증권시장의 1980년 1월 5일부터 1996년 말까지 총 4,982일 동안의 일별종합주가지수를 대수수익률로 전환한 시계열자료로 R/S분석한 결과 안정성과 주기유무를 판별하는 V-통계량 그래프에 의하면 83일과 33일의 비주기적 순환을 나타내고 있음을 알 수 있었다. 이러한 분석결과는 가우시안 랜덤과정과 그다지 큰 차이가 나지 않음을 알 수 있었다. 또한 선형성을 제거한 ARMA잔차와 비선형성을 제거한 GARCHM잔차자료에 대한 R/S분석한 결과도 원래 시계열보다 더 가우시안 랜덤과정에 더 근접함을 알 수 있었다. 한편 총 10개의 대리자료를 만들어서 평균을 취한 값으로 분석한 결과도 마찬가지로 나타나고 있다. 일별주가지수수익률에 내재하는 선형성분을 ARMA과정에 의정에 제거하고 남은 잔차중에는 비선형성분이 여전히 잔존하는데 그것이 일부 GARCHM과정에 의해서 미미하고 가우시안 랜덤과정이 보다 크게 나타남을 알 수 있었다.

• Science of Emotion and Sensibility
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• v.2 no.1
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• pp.53-60
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• 1999

EEG 생리신호의 분석은 국내에서도 최근에 활발하게 연구가 진행되고 있으나, 시계열을 이용한 분석법은 통계학의 전문적인 지식을 요구하고 있기 때문에 연구에 많은 어려움이 있다. 그러므로 감성과학 연구자들이 보다 쉽게 이해하고 분석할 수 있는 Tool의 개발이 절실히 요구되고 있다. 본 논문에서는 EEG 생리신호 분석을 위한 모형분석 시스템과 생리신호 분류를 위한 판별분류 시스템을 구축하였다. 이 시스템에서는 신호분석을 위한 그래프 작성, 자극 신호에 대한 모형식별 방법의 제시, 모형에 대한 추정 및 진단 기준에 따른 최적의 모형선정 방법 등을 지원한다. 또한 선정된 모형에 이해 모수를 추정하고 이를 이용하여 통계에 대한 지식이 없이도 쉽게 각 뇌파 신호들을 판별 분류할 수 있다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1313-1325
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• 2017

Economic statistics such as GDP, consumer prices, balance of payments, and unemployment rates are regularly measured over time. One of the best way to understand economic statistics is to visualize economic statistics as a picture. This makes it easier to grasp patterns of economic statistics and to communicate with users. The web technologies and the visualization tools make it possible to create dynamic and interactive visualization of economic statistics. Statistics Korea and the Bank of Korea provide various data visualization relating to official statistics such as infographics and dynamic charts. This paper presents an overview of visualization of Statistics Korea and the Bank of Korea. It also discusses a future direction to explore the visualization of Korean economic statistics.

• International Area Studies Review
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• v.13 no.3
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• pp.287-308
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• 2009

This article examines the distributional characteristics of the return of Chinese stock market indices. The majority of previous empirical researches have tended to focus upon the simple stock market index. However, this study focuses on the four indices which represent the characteristics of each stock market index. The empirical findings indicate that the returns of the four chinese indices are not normally distributed at conventional levels. The Ljimg-Box -statistics indicate the returns of the index of A shares are not serially autocorrelated. However, the returns of the index of B shares are serially autocorrelated. The empirical findings also indicate returns of the four chinese indices are not serially autocorrelated. The statistics of Regression Specification Error Test and ARCH indicate the returns of all four indices are not serially linear. The findings also indicate that E- GARCH model is the most fittest model for the returns of the four chinese indices and the forecast error can be reduced by using student t distribution rather normal distribution.