• 제목/요약/키워드: ARMA

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ARMA Model Identification Using the Bayes Factor

  • Son, Young-Sook
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.503-513
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    • 1999
  • The Bayes factor for the identification of stationary ARM(p,q) models is exactly computed using the Monte Carlo method. As priors are used the uniform prior for (\ulcorner,\ulcorner) in its stationarity-invertibility region, the Jefferys prior and the reference prior that are noninformative improper for ($\mu$,$\sigma$\ulcorner).

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Estimation of Parameters in Fuzzy Time Series Model with Triangular Fuzzy Numbers

  • 손은희;손건태
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2000년도 추계학술발표회 논문집
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    • pp.267-269
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    • 2000
  • Using the fuzzified coefficients, ARMA processes can be extended to fuzzy time series model. In this paper, the estimation of parameters in the fuzzy time series model with asymmetric triangular fuzzy coefficients is studied. Nonlinear programming is applied to get solutions of parameters.

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A Comparative Study of the GPAC Method and the 3-pattern Method for Identifying ARMA Processes

  • Chul Eung KIM;ByoungSeon CHOI
    • Communications for Statistical Applications and Methods
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    • 제3권3호
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    • pp.47-58
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    • 1996
  • The generalized partial autocorrelation (GPAC) method of Woodward and Gray (1981) and the 3-pattern method of Choi (1991) have been used for identifying ARMA processes. The methods are based on the extended Yule-Walker equations. The purpose of this paper is to show the 3-pattern method is superior to the GPAC method through theoretical analysis and computer simulations.

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Dependence structure analysis of KOSPI and NYSE based on time-varying copula models

  • Lee, Sangyeol;Kim, Byungsoo
    • Journal of the Korean Data and Information Science Society
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    • 제24권6호
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    • pp.1477-1488
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    • 2013
  • In this study, we analyze the dependence structure of KOSPI and NYSE indices based on a two-step estimation procedure. In the rst step, we adopt ARMA-GARCH models with Gaussian mixture innovations for marginal processes. In the second step, time-varying copula parameters are estimated. By using these, we measure the dependence between the two returns with Kendall's tau and Spearman's rho. The two dependence measures for various copulas are illustrated.

오프셋 제거방식을 이용한 상호연관 시스템의 적응제어 (Self Tuning Control of Interconnected System wsing Offset Rejection Techniques)

  • 양흥석;김영철;박용식
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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    • pp.214-217
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    • 1987
  • In this paper self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in multiple ARMA process. This process is simplified as independent SISO ARMA process having offset terms. This offset was considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the parameter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results considers well with the analysis in case of linear interconnection.

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오프셋 모형화 기법을 이용한 상호연관 시스템의 분산형 적응제어 (Decentralized Adaptive Control of Interconnected System using Off-Set Modeling)

  • 양흥석;박용식;주성순
    • 대한전기학회논문지
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    • 제37권12호
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    • pp.879-883
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    • 1988
  • In this paper, self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in MIMO ARMA procss. This process is simlified as independent SISO ARMA processes having offset terma, which are considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the paramter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results consider well with the analysis in case of linear interconnection.

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AUTOCORRELATION FUNCTION STRUCTURE OF BILINEAR TIME SREIES MODELS

  • Kim, Won-Kyung
    • Journal of the Korean Statistical Society
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    • 제21권1호
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    • pp.47-58
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    • 1992
  • The autocorrelation function structures of bilinear time series model BL(p, q, r, s), $r \geq s$ are obtained and shown to be analogous to those of ARMA(p, l), l=max(q, s). Simulation studies are performed to investigate the adequacy of Akaike information criteria for identification between ARMA(p, l) and BL(p, q, r, s) models and for determination of orders of BL(p, q, r, s) models. It is suggested that the model of having minimum Akaike information criteria is selected for a suitable model.

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스펙트럼 추정을 위한 근사 과결정 방식 (Approximate Overdetermined Method for Spectral Estimation)

  • 이철희;정찬수;양흥석
    • 대한전기학회논문지
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    • 제37권4호
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    • pp.232-239
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    • 1988
  • The approximate overdetermined method is proposed for high resolution spectral estimation in case of short data record length or narrow band signal. And a new recursive AR parameter estimation is derived in the form of fast algorithm. For ARMA spectral estimation, two stage procedure is used in estimating ARMA parameters. First AR parameters are estimated by using the modified Yule-Walker equations, and then MA parameters are implicitly estimated by estimating numerator spectral(NS) coefficients.

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