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Efficient computation for Whittaker-Henderson smoothing

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  • Weinert, Howard L.

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  • Weinert, Howard L., 2007. "Efficient computation for Whittaker-Henderson smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 959-974, October.
    • Handle: RePEc:eee:csdana:v:52:y:2007:i:2:p:959-974
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    References listed on IDEAS

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    1. 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.
    2. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    3. Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May.
    4. Verrall, R. J., 1993. "A state space formulation of Whittaker graduation, with extensions," Insurance: Mathematics and Economics, Elsevier, vol. 13(1), pages 7-14, September.
    5. 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.
    6. Brooks, R. J. & Stone, M. & Chan, F. Y. & Chan, L. K., 1988. "Cross-validatory graduation," Insurance: Mathematics and Economics, Elsevier, vol. 7(1), pages 59-66, January.
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    Cited by:

    1. Garcin, Matthieu, 2017. "Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 462-479.
    2. Dermoune Azzouz & Djehiche Boualem & Rahmania Nadji, 2009. "Multivariate Extension of the Hodrick-Prescott Filter-Optimality and Characterization," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-35, May.
    3. Hiroshi Yamada, 2025. "Linear Trend, HP Trend, and bHP Trend," Mathematics, MDPI, vol. 13(11), pages 1-15, June.
    4. Hiroshi Yamada, 2023. "Quantile regression version of Hodrick–Prescott filter," Empirical Economics, Springer, vol. 64(4), pages 1631-1645, April.
    5. Garcia, Damien, 2010. "Robust smoothing of gridded data in one and higher dimensions with missing values," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1167-1178, April.
    6. Hiroshi Yamada & Ruoyi Bao, 2022. "$$\ell _{1}$$ ℓ 1 Common Trend Filtering," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1005-1025, March.
    7. Weinert, Howard L., 2009. "A fast compact algorithm for cubic spline smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 932-940, February.
    8. Ruixue Du & Hiroshi Yamada, 2020. "Principle of Duality in Cubic Smoothing Spline," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    9. Zihan Jin & Hiroshi Yamada, 2024. "Boosted Whittaker–Henderson Graduation," Mathematics, MDPI, vol. 12(21), pages 1-18, October.

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