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A Unit Root Test via a Discrete Cosine Transform
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 Title & Authors
A Unit Root Test via a Discrete Cosine Transform
Lee, Go-Un; Yeo, In-Kwon;
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 Abstract
In this paper, we introduce a unit root test via discrete cosine transform in the AR(1) process. We first investigate the statistical properties of DCT coefficients under the stationary AR(1) process and the random walk process in order to verify the validity of the proposed method. A bootstrapping approach is proposed to induce the distribution of the test statistic under the unit root. We performed simulation studies for comparing the powers of the Dickey-Fuller test and the proposed test.
 Keywords
Dickey-Fuller test;parametric bootstrap;random walk;
 Language
Korean
 Cited by
 References
1.
여인권, 윤화형, 조신섭 (2006). 시계열분석을 위한 주파수 공간상에서의 재표집 기법, <응용통계연구>, 19, 121-134. crossref(new window)

2.
Ahmed, N., Natarjan, T. and Rao, K. R. (1974). Discrete cosine transform, IEEE Transactions on Computers, 23, 90-93. crossref(new window)

3.
Davies, R. B. (2001). Integrated processes and the discrete cosine transform, Journal of Applied Probability, 38A, 701–717.

4.
Dickey, D. A., Bell, W. R. and Miller, R. B. (1986). Unit roots in time series models: Tests and implications, The American Statistician, 40, 12-26. crossref(new window)

5.
Dickey, D. A. and Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root, Journal of the American Statistical Association, 74, 427-431. crossref(new window)

6.
Hamilton, J. D. (1994). Time Series Analysis, Princeton University Press.

7.
Harvey, A. C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter, Cambridge University Press, Cambridge.

8.
Phillips, P. C. B. and Perron, P. (1988). Testing for unit roots in time series regression, Biometrika, 75, 335-346. crossref(new window)

9.
Rao, K. R. and Yip, P. (1990). Discrete Cosine Transform: Algorithms, Advantages, Applications, Academic Press, New York.