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Jump process for the trend estimation of time series

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  • Zhao, Shan
  • Wei, G. W.

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  • Zhao, Shan & Wei, G. W., 2003. "Jump process for the trend estimation of time series," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 219-241, February.
    • Handle: RePEc:eee:csdana:v:42:y:2003:i:1-2:p:219-241
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    1. Ferreira, Eva & Nunez-Anton, Vicente & Rodriguez-Poo, Juan, 2000. "Semiparametric approaches to signal extraction problems in economic time series," Computational Statistics & Data Analysis, Elsevier, vol. 33(3), pages 315-333, May.
    2. Wen, Yi & Zeng, Bing, 1999. "A simple nonlinear filter for economic time series analysis," Economics Letters, Elsevier, vol. 64(2), pages 151-160, August.
    3. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    4. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    5. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    6. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    7. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    8. Borra, Simone & Di Ciaccio, Agostino, 2002. "Improving nonparametric regression methods by bagging and boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 407-420, February.
    9. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
    10. Sims, Christopher A & Uhlig, Harald, 1991. "Understanding Unit Rooters: A Helicopter Tour," Econometrica, Econometric Society, vol. 59(6), pages 1591-1599, November.
    11. Host, Gudmund, 1999. "Kriging by local polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 29(3), pages 295-312, January.
    12. Cox, John C. & Ross, Stephen A., 1976. "The valuation of options for alternative stochastic processes," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 145-166.
    13. Marco Bianchi & Martin Boyle & Deirdre Hollingsworth, 1999. "A comparison of methods for trend estimation," Applied Economics Letters, Taylor & Francis Journals, vol. 6(2), pages 103-109.
    14. Doksum, Kjell & Koo, Ja-Yong, 2000. "On spline estimators and prediction intervals in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 35(1), pages 67-82, November.
    15. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    16. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    17. Keilegom, Ingrid Van & Akritas, Michael G. & Veraverbeke, Noel, 2001. "Estimation of the conditional distribution in regression with censored data: a comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 35(4), pages 487-500, February.
    18. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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    Cited by:

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    2. Fried, Roland, 2007. "On the robust detection of edges in time series filtering," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 1063-1074, October.

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