• 농촌계획
• /
• 제17권1호
• /
• pp.1-11
• /
• 2011

본 연구에서는 ARIMA(Autoregressive Integrated Moving Average) 모델을 이용하여 농촌관광마을의 월별 관광객을 추정하였다. 단일 마을에 대한 시계열 자료를 경상북도 안동시에 위치한 하회마을을 대상으로 구축하였다. 월별 시계열 자료는 2000년부터 2010년까지 구성되었는데(2008년도 누락), 2000년에서 2007년까지 자료는 최적 모델의 도출에 나머지는 예측치의 검정에 사용되었다. 연구 결과 최적모델에 필요한 시계열 자료의 길이는 6년으로 나타났으며, 최적모델은 계절성을 고려한 SARIMA(2,1,1)(1,1,2)12로 나타났다. 최적 시계열 년수로 나타난 6년을 사용하여 2000-2005, 2001-2006, 그리고 2002-2007의 자료로부터 각각 SARIMA(2,1,1)(1,1,2)12를 도출하여, 차기년도들에 대한 예측결과를 비교한 결과, 높은 $R^2$값을 보였다.

• 응용통계연구
• /
• 제21권3호
• /
• pp.387-397
• /
• 2008

최근 공간통계를 이용한 많은 연구가 진행되고 있고 공간통계학을 접목한 소지역 추정(small area estimation) 방법이 좋은 결과를 주고 있는 것으로 알려져 있다 소지역 추정에 사용되는 격자자료(lattice data) 분석에서 이웃정보를 정의하는 것은 자료 분석의 성패를 결정짓는 매우 중요한 부분이다. 그러나 기존에 사용된 대부분의 이웃정보시스템은 경계선을 공유할 때 이웃으로 정하는 방법을 사용하고 있다. 이에 본 논문에서는 경계선 공유를 이용한 이웃정보시스템 뿐 아니라 다른 여러 이웃정보시스템을 구하는 방법을 설명하고 2001년 경제활동자료를 이용하여 이 시스템들을 비교하였다

• 한국전자통신학회논문지
• /
• 제11권11호
• /
• pp.1069-1076
• /
• 2016

최근 비쥬얼 센서 기술의 발달로 센서 네트워크에 영상을 추가하기 위한 다양한 연구가 진행되고 있다. 비쥬얼 센서는 다른 센서 정보에 비해 데이터가 크기 때문에 데이터의 크기를 효율적으로 관리하는 것이 무엇보다 중요하다. 본 논문에서는 효과적인 데이터 관리에 필요한 비디오 트래픽 예측 방법을 제안한다. 제안하는 방법은 비디오 센서에서 획득되는 영상의 특성을 반영하여 1차 AR 모델로 비디오 트래픽을 모델링하고 칼만필터 알고리즘을 적용하여 트래픽을 예측한다. 제안하는 방법은 계산량이 많지 않아 센서 노드에 적용되기 적합하다. 실험 결과는 제안하는 방법이 비교적 간단한 형태이지만 전체 평균 트래픽의 1% 이내로 오차로 정확하게 트래픽을 예측하는 것을 보여준다.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권9호
• /
• pp.201-208
• /
• 2020

Terms of trade is an important indicator of the welfare gains from international trade to the exporting country. Terms of trade of oil-exporting countries are hypothesized to depend primarily on oil prices. The study assesses the relation between oil prices and the terms of trade of Saudi Arabia. The study uses the Autoregressive Distributed Lag method to determine the cointegration between the country's terms of trade and oil prices for the period 2000-2018. The data for net barter terms of trade is taken from World Development Indicators and oil price is taken from Saudi Arabian Monetary Agency. The results show that oil prices and terms of trade are cointegrated and any disequilibrium between the two variables is corrected by 35% in a year. The study also reports a positive relationship between the two items, both in the short run and long run. Diagnostic tests indicate the model to be fit. The results suggest that, for a primarily oil-producing country like Saudi Arabia, the terms of trade depend on oil prices. The study fills the gap in the literature on the study of terms of trade for Saudi Arabia for the last few years, where there has been a high volatility in oil prices.

• 응용통계연구
• /
• 제33권3호
• /
• pp.297-308
• /
• 2020

본 논문에서는 고빈도 함수적 ARCH 모형을 소개하고 근사모형으로써 다변량 변동성 모형을 고려하였다. 이를 기반으로 함수형 변동성 분석에서 중요한 요소인 일중 로그 수익률의 적절한 시간 간격을 찾아보았다. 또한 함수적 ARCH 모형에서 l-시차 후 변동성 예측식을 제시하고 고빈도 KOSPI 자료에 적합하여 예시하였다.

• International Journal of Aeronautical and Space Sciences
• /
• 제11권4호
• /
• pp.326-337
• /
• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Communications for Statistical Applications and Methods
• /
• 제16권1호
• /
• pp.31-40
• /
• 2009

공간시계열모형은 공간의 위치와 시간의 흐름에 따라 동시에 관측되는 분야인 기상, 지질, 천문, 생태, 역학 등에서 넓이 사용되고 있는 매우 복잡한 모형이다. 본 논문은 공간시계열모형에 대한 모수 추정에 있어서 기존의 최대우도추정 방법이 가지는 컴퓨팅의 문제를 해결하기 위하여 모수에 대한 사전정보와 자료의 정보를 모두 이용하는 깁스샘플링과 같은 MCMC 방법으로 모수를 추정하고, 실제 적용사례분석으로 여러 가지 측도를 구해서 추정된 모수에 대한 수렴진단을 수행하였다.

• 비파괴검사학회지
• /
• 제36권2호
• /
• pp.93-101
• /
• 2016

This paper presents the results obtained using time-series-based methods for structural damage assessment. The methods are applied to a wind turbine blade structure subjected to fatigue loads. A 9 m CX-100 (carbon experimental 100 kW) blade is harmonically excited at its first natural frequency to introduce a failure mode. Consequently, a through-thickness fatigue crack is visually identified at 8.5 million cycles. The time domain data from the piezoelectric active-sensing techniques are measured during the fatigue loadings and used to detect incipient damage. The damage-sensitive features, such as the first four moments and a normality indicator, are extracted from the time domain data. Time series autoregressive models with exogenous inputs are also implemented. These features could efficiently detect a fatigue crack and are less sensitive to operational variations than the other methods.

• 동아시아경상학회지
• /
• 제6권4호
• /
• pp.35-45
• /
• 2018

Purpose - The operating mechanism between education input and economic growth is a mysterious proposition that has attracted a vast array of scholars' interests to study on it. Therefore, this paper sets China as an example to analyze the dynamic relationship between education input and economic growth. Research design and methodology - The annual time series from 1990 to 2017 will be employed to conduct an empirical analysis under the vector autoregressive model. The education input is treated as an factor that impacts the economic growth such as labor input and capital input. Meanwhile, the education input will be added to the Cobb-Douglas production function to form a new one so as to explore the dynamic relationship between education input and economic growth. Results - According to the results of empirical analysis, it can be found that the education input has an increasingly positive effect on economic growth. Simultaneously, the economic growth also has a positive effect on education input, but this kind of effect is not steady. Of course, the labor input and the capital input also can promote the economic growth to some degree. Conclusions - The education input is one of most important inputs for a country. Based on the empirical analysis, this paper suggests that the China's government should put more emphasis on the education input so to make its economy develop well.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권11호
• /
• pp.607-617
• /
• 2020

This study investigates the causal relationship between public and private external debt and economic growth in developing countries. Our model includes 18 selected Asian developing and transition economies from 1995 thru 2019. We employ the dynamic heterogeneous panel data methods, pooled mean group (PMG), robust cross-sectional augmented autoregressive distributed lag (CS-ARDL), and pairwise panel causality test. The results of PMG and CS-ARDL show the existence of causality between external debt and economic growth both in the short-run and long-run. The pairwise Granger causality test found the bidirectional causal relationship runs from total external debt, public external debt, and private external debt to economic growth and economic growth to external debt. The results showed first the existence of causality in the short-run and long-run between external debt and economic growth and the second, bi-directional causality that runs from external debt to economic growth and economic growth to external debt. Both the dynamic models and robust estimator found the same inferences about the impact of main variables on economic growth in Asian developing and transition economies. The findings of this study suggest to assure debt management, investment in productive sectors, increase domestic savings, decrease external dependency, and focus on international trade.