• Title/Summary/Keyword: Run 시계열

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Bootstrap estimation of long-run variance under strong dependence (장기간 의존 시계열에서 붓스트랩을 이용한 장기적 분산 추정)

  • Baek, Changryong;Kwon, Yong
    • The Korean Journal of Applied Statistics
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    • v.29 no.3
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    • pp.449-462
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    • 2016
  • This paper considers a long-run variance estimation using a block bootstrap method under strong dependence also known as long range dependence. We extend currently available methods in two ways. First, it extends bootstrap methods under short range dependence to long range dependence. Second, to accommodate the observation that strong dependence may come from deterministic trend plus noise models, we propose to utilize residuals obtained from the nonparametric kernel estimation with the bimodal kernel. The simulation study shows that our method works well; in addition, a data illustration is presented for practitioners.

Estimation of Air Travel Demand Models and Elasticities for Jeju-Mainland Domestic Routes (제주-내륙 간 국내선 항공여객수요모형 및 탄력성의 추정)

  • Baek, Seung-Han;Kim, Sung-Soo
    • Journal of Korean Society of Transportation
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    • v.26 no.1
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    • pp.51-63
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    • 2008
  • Jeju-Mainland demand for air passenger is variated by the season because most of the demands stem from the leisure travel. This research is to estimate the econometrics demand models(A simple time series model and the partial adjustment model) and elasticities of each models for the Jeju-Mainland domestic routes air travel market using the time series aggregate data between the year 1996 and 2005. As the result of estimating, income elasticity was evaluated to be elastic(1.55) and fare elasticity was inelastic(-0.49${\sim}$-0.59) for A simple time series models. In the partial adjustment model's case, income elasticity was evaluated to be inelastic(0.51) in short-run whereas it was evaluated to be elastic(1.88) in long-run. Fare elasticity was evaluated to be inelastic in short-run(high-demand season: -0.13, slack season: -0.20) and long-run(high-demand season: -0.48, slack season: -0.72).

The forecasting evaluation of the high-order mixed frequency time series model to the marine industry (고차원 혼합주기 시계열모형의 해운경기변동 예측력 검정)

  • KIM, Hyun-sok
    • The Journal of shipping and logistics
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    • v.35 no.1
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    • pp.93-109
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    • 2019
  • This study applied the statistically significant factors to the short-run model in the existing nonlinear long-run equilibrium relation analysis for the forecasting of maritime economy using the mixed cycle model. The most common univariate AR(1) model and out-of-sample forecasting are compared with the root mean squared forecasting error from the mixed-frequency model, and the prediction power of the mixed-frequency approach is confirmed to be better than the AR(1) model. The empirical results from the analysis suggest that the new approach of high-level mixed frequency model is a useful for forecasting marine industry. It is consistent that the inclusion of more information, such as higher frequency, in the analysis of long-run equilibrium framework is likely to improve the forecasting power of short-run models in multivariate time series analysis.

-Mathematical models for time series of monthly Precipitation and monthly run-off on South Han river basin- (남한강수계의 월강우량과 월유출량의 시계별 산술모형)

  • 이종남
    • Water for future
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    • v.14 no.2
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    • pp.71-79
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    • 1981
  • This study is established of simulation models form the stochastic and statistic analysis of monthly rainfall and monthly runoff on south Han river. The time series simulation of monthly runoff is introduced with a linear stochastic model for simulating synthetic monthly runoff data. And, time series model of monthly pricipitation and monthly runoff is introduced to be a pure random time series with known statical parameter, which is characterized by an exponential recession curve with one parameter, and is develope expressing the statistical parameter for length of carryover.

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Estimation of city gas demand function using time series data (시계열 자료를 이용한 도시가스의 수요함수 추정)

  • Lee, Seung-Jae;Euh, Seung-Seob;Yoo, Seung-Hoon
    • Journal of Energy Engineering
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    • v.22 no.4
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    • pp.370-375
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    • 2013
  • This paper attempts to estimate the city gas demand function in Korea over the period 1981-2012. As the city gas demand function provides us information on the pattern of consumer's city gas consumption, it can be usefully utilized in predicting the impact of policy variables such as city gas price and forecasting the demand for city gas. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the city gas demand function. The results show that short-run price and income elasticities of the city gas demand are estimated to be -0.522 and 0.874, respectively. They are statistically significant at the 1% level. The short-run price and income elasticities portray that demand for city gas is price- and income-inelastic. This implies that the city gas is indispensable goods to human-being's life, thus the city gas demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for city gas is price- and income-elastic in the long-run.

Effects of Parameter Estimation in Phase I on Phase II Control Limits for Monitoring Autocorrelated Data (자기상관 데이터 모니터링에서 일단계 모수 추정이 이단계 관리한계선에 미치는 영향 연구)

  • Lee, Sungim
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.1025-1034
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    • 2015
  • Traditional Shewhart control charts assume that the observations are independent over time. Current progress in measurement and data collection technology lead to the presence of autocorrelated process data that may affect poor performance in statistical process control. One of the most popular charts for autocorrelated data is to model a correlative structure with an appropriate time series model and apply control chart to the sequence of residuals. Model parameters are estimated by an in-control Phase I reference sample since they are usually unknown in practice. This paper deals with the effects of parameter estimation on Phase II control limits to monitor autocorrelated data.

Drought frequency analysis for multi-purpose dam inflow using bivariate Copula model (이변량 Copula 모형을 활용한 다목적댐 유입량 가뭄빈도해석)

  • Sung, Jiyoung;Kim, Eunji;Kang, Boosik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.340-340
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    • 2021
  • 가뭄의 특성상 시점과 종점을 명확하게 정의하기 어렵기 때문에 기준수문량을 설정하고 부족량과 지속기간을 정의하는 것이 일반적이다. 대상 수문량은 강우나 유출량을 사용할 수 있지만, 두 성분간 지체와 감쇄효과로 인하여 빈도해석의 결과는 차이를 보일 수 밖에 없어, 사용 목적에 따라 선별적으로 적용해야 한다. 가뭄빈도해석은 강우를 기반으로 지속기간과 심도를 정의하여 빈도를 해석하는 연구가 선행되어왔지만, 기본적으로 강우의 간헐적 발생특성과 체감도의 한계가 문제로 지적되고 있다. 본 연구에서는 댐 유입량의 Run 시계열 특성을 이용하여 다양한 유황을 기준유량으로 활용하여 가뭄의 시점과 종점에 대한 가뭄사상을 추출하고 지속기간과 누적부족량을 계산하여 가뭄빈도해석의 변수로 설정하였다. 두 변수간의 복잡한 상호 관계를 해석하기 위해 Copula 함수를 이용한 이변량 가뭄빈도해석을 진행하였다. 먼저 소양강댐('74-'19) 유입량, 충주댐('86-'19) 유입량을 연구대상지역으로 설정하여, 두 유역의 유입량의 추세분석을 통해 시간의존성을 파악하였다. 유황분석에 사용되는 분위량중 평수량을 기준값으로 사용하여 각 년별 최대 지속기간과 누적부족량을 추출하였다. Copula 가뭄빈도해석을 수행하기 전에 지속기간에는 GEV, 누적 부족량에는 Log-normal 분포를 적용해 단변량 누적확률분포를 계산하여 재현기간을 도출하였다. 이변량 빈도해석에 Clayton Copula 함수를 적용하여 가뭄빈도해석을 진행하였고, Copula 이변량 재현기간과 SDF곡선을 도출하였다. Clayton Copula를 이용한 이변량 가뭄빈도해석의 결과로 소양강댐의 가장 극심한 가뭄은 1996년으로 단변량 재현기간은 지속기간 기준 9.11년, 누적부족량 기준 17.26년, Copula 재현기간은 141.19년 이며 충주댐의 가장 극심한 가뭄은 2014년으로 단변량 재현기간은 지속기간 기준 17.76년, 누적부족량 기준 18.72년, Copula 재현기간은 184.19년으로 단변량 가뭄빈도해석을 통한 재현기간보다 Copula 재현기간이 높은 결과가 도출되었다. Run 시계열을 바탕으로 한 기준유량의 임계값 기준 Event 산정과 Copula를 이용한 빈도해석은 가뭄분석에 이용되는 자료의 상관관계와 분포특성을 재현하는데 효과적인 특징이 있다. 이를 미루어 보아 Copula 함수를 이용한 가뭄빈도해석의 재현기간은 보다 현실적인 재현기간을 도출할 수 있는 것으로 판단된다. 임계값의 조정을 통해 가뭄빈도해석의 변수의 양이 늘어나면, 보다 정확도 높은 재현기간을 도출하여 수문학적 가뭄을 정의할 수 있을 것이라고 사료된다.

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Average Run Lengths of Special-Cause Control Charts for Autocorrelated Processes (자동상관인 공정에서 Special-Cause CUSUM 관리도의 ARL)

  • Sungwoon Choi
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.18 no.36
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    • pp.243-251
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    • 1995
  • 본 연구에서는 자동상관인 공정의 변화를 빠르게 탐지할 수 있는 Special-Cause CUSUM 관리도를 사용하여 다섯가지 시계열 모델에 대해 다음과 같은 연구를 수행한다. 첫째 ACF와 PACF로 파라미터에 따른 ARL의 변화를 쉽게 해석할 수 있는 방법과 둘째로 독립인 관측값에 적용하는 Hawkins(1992)의 ARL 간략계산법을 자동상관인 공정에서도 사용할 수 있는 기법을 제시하여 기존의 시뮬레이션을 이용한 ARL 계산법에 비해 빠르고도 정확한 값을 구한다. 끝으로 두가지 유형의 평균이동에 대한 ARL 변화를 각각 계산해 보아 그 효과를 비교분석 한다.

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고령화가 가정부문 에너지 소비량에 미치는 영향 분석: 전력수요를 중심으로

  • Won, Du-Hwan
    • Environmental and Resource Economics Review
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    • v.21 no.2
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    • pp.341-369
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    • 2012
  • Population aging has been one of the serious problems in Korea. Aging can affect social and economic features including energy consumption. This paper analyzed how population aging makes an effect on residential electricity demand. Yearly data from 1965 to 2010 were collected. The long and short-run demands for residential electricity were estimated with respect to Korean aging index. The results show that population aging reduces residential electricity demands in the short run significantly, but the effect decreases in the long run. However, population aging still negatively affects residential electricity consumption in long run. If population keep aging as Korean government expected, then the residential electricity demand per capita will grow less than 3%.

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The Impact of the Supply Regulation on the Price in Farming Olive Flounder (출하량 조절이 양식 넙치가격에 미치는 영향)

  • Kang, Seokkyu
    • Environmental and Resource Economics Review
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    • v.24 no.4
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    • pp.709-725
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    • 2015
  • This study is to analyse the relationship between the price and the supply in the farming Olive Flounder's production area market. The data used in this study correspond to daily price and supply quantity covering time period from January 1, 2007 to June 30. 2013. The analysis methods of cointegration and vector error correction model are employed. The empirical results of this study are summarized as follows: First, the price and the supply follow random walks and they are integrated of order 1. Second, the price and the supply are cointegrated. Third, vector error correction model suggests that the relationship between the price change ration and the supply quantity change ratio has negative and feedback effect exists in the long-run, but the disequilibrium between the price and the supply is corrected by the supply quantity. Finally, vector error correction model suggests that the supply quantity leads the price in the short-run. This indicates that the decrease(increase) of the supply quantity results in the increase(decrease) of the price.