• 응용통계연구
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• 제22권6호
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• pp.1191-1201
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• 2009

공정관리에서 작은 평균변화를 탐지하기 위하여 누적합 관리도를 사용하는 것이 일반적이다. 자기상관이 존재하는 공정의 경우 시계열 모형에 적합하여 구한 잔차를 관리도에 적용하는 모형기반 관리방법이 활용되고 있다. 그러나 공정에 일정한 크기의 지속적인 수준 변화가 발생하면 잔차에는 동적 평균변화의 패턴이 나타나게 되어 누적합 관리도의 탐지능력은 저하될 수 있다. 본 논문에서는 잔차에 등락을 반복하는 진동(oscillation) 특성의 동적 평균변화가 발생하는 ARMA(1,1) 모형을 대상으로, 그러한 변화를 효율적으로 탐지할 수 있는 새로운 OCUSUM 관리도를 제안하고 모의실험을 통해 최근에 소개된 기존의 CUSUM 관리도와 탐지능력을 비교하였다.

• 수산경영론집
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• 제52권4호
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• pp.13-28
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• 2021

The purpose of this study is to compare short-term price predictive power among ARMA ARMAX and VAR forecasting models based on the MDM test using monthly consumer price data of frozen mackerel. This study also aims to help policymakers and economic actors make reasonable choices in the market on monthly consumer price of frozen mackerel. To analyze this study, the frozen wholesale prices and new consumer prices were used as variables while the price time series data were used from December 2013 to July 2021. Through the unit root test, it was confirmed that the time series variables employed in the models were stable while the level variables were used for analysis. As a result of conducting information standards and Granger causality tests, it was found that the wholesale prices and fresh consumer prices from the previous month have affected the frozen consumer prices. Then, the model with the highest predictive power was selected by RMSE, RMSPE, MAE, MAPE, and Theil's inequality coefficient criteria where the predictive power was compared by the MDM test in order to examine which model is superior. As a result of the analysis, ARMAX(1,1) with the frozen wholesale, ARMAX(1,1) with the fresh consumer model and VAR model were selected. Through the five criteria and MDM tests, the VAR model was selected as the superior model in predicting the monthly consumer price of frozen mackerel.

• 한국국방경영분석학회지
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• 제8권1호
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• pp.71-76
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• 1982

A procedure is established for combining a regression model and a time series model to fit to a set of autocorrelated data. This procedure is based on an iterative method to compute regression parameter estimates and time series parameter estimates simultaneously. The time series model which is discussed is basically AR(p) model, since MA(q) model or ARMA(p,q) model can be inverted to AR({$\infty$) model which can be approximated by AR(p) model. The procedure discussed in this articled is applied in general to any combination of regression model and time series model.

• 대한산업공학회지
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• 제14권1호
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• pp.51-56
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• 1988

A spectrum analysis method is presented with an example as an aid to Box and Jerkins' model identification procedure, where the theoretical spectrum of ARMA model and its confidence intervals derived by chi-square distribution are compared. An APL (A Programming Language) program for the method is developed for the 16-bit personal computer.

• Journal of the Korean Data and Information Science Society
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• 제18권1호
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• pp.195-210
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• 2007

This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity ($\beta$-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.

• 한국정밀공학회지
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• 제8권4호
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• pp.76-83
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• 1991

자기회귀-이동평균모델에 의하여 시스템의 파라미터를 추정할 수 있는 벡터채널 원형 격자 필터(vector channel circular lattice filter)의 알고리즘을 제시하였다. 이 알고리즘은 스칼라 연산만으로 이루어져 계산이 간단한 장점이 있다. 3자유도 시스템의 시뮬레이션 결과로부터 격자 필터의 성능을 검증하였으며, 1자유도 팔의 고유진동수와 감쇄비를 추정하였다.

• Journal of applied mathematics & informatics
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• 제12권1_2호
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• pp.67-79
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• 2003

An approximation for the bias in lag window estimators of the degree of differencing in fractionally integrated time series models is derived. The expression obtained is compared with the observed bias from simulations for various windows.

• Korean Journal of Mathematics
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• 제26권2호
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• pp.155-166
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• 2018

Consider FARIMA time series with innovations that have infinite variances. We are interested in the estimation of self-similarities $H_n$ of FARIMA(0, d, 0) by using modified R/S statistic. We can confirm that the $H_n$ converges to Hurst parameter $H=d+\frac{1}{2}$. Finally, we figure out ARMA and minimum variance power spectrum density of FARIMA processes.

• 품질경영학회지
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• 제15권1호
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• pp.47-54
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• 1987

It is common that the process capability fluctuates as time passes, but concentrates to the mean value. To keep up process capability with given limits is vital to stability of process. Various control charts, especially ${\sigma}-chart$, have been used for analyzing process capability, but It sometimes can not give distinct answer. So this paper introduces another analyzing method by ARMA (autoregressive moving average) which is originally developed for forecasting, and demonstrates the analyzing methodology through a case study.

• 한국음향학회지
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• 제3권1호
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• pp.25-35
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• 1984

This paper analysis the Dynamic Time Warping algorithms for time normalization of speech pattern and discusses the Dynamic Programming algorithm for spoken Korean isolated digits recognition. In the DP matching, feature vectors of the reference and test pattern are consisted of first three formant frequencies extracted by power spectrum density estimation algorithm of the ARMA model. The major differences in the various DTW algorithms include the global path constrains, the local continuity constraints on the path, and the distance weighting/normalization used to give the overall minimum distance. The performance criterias to evaluate these DP algorithms are memory requirement, speed of implementation, and recognition accuracy.