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Kolmogorov-Wiener Filters for Finite Time Series

Author

Listed:
  • Christoph Schleicher

Abstract

No abstract is available for this item.

Suggested Citation

  • Christoph Schleicher, 2003. "Kolmogorov-Wiener Filters for Finite Time Series," Computing in Economics and Finance 2003 109, Society for Computational Economics.
    • Handle: RePEc:sce:scecf3:109
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    Citations

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    Cited by:

    1. Ard den Reijer, 2006. "The Dutch business cycle: which indicators should we monitor?," DNB Working Papers 100, Netherlands Central Bank, Research Department.
    2. Dimitrios D. Thomakos, 2008. "Optimal Linear Filtering, Smoothing and Trend Extraction for Processes with Unit Roots and Cointegration," Working Paper series 14_08, Rimini Centre for Economic Analysis.
    3. repec:rdg:wpaper:em-dp2013-04 is not listed on IDEAS
    4. Andrle, Michal, 2012. "Understanding DSGE Filters in Forecasting and Policy Analysis," Dynare Working Papers 16, CEPREMAP.
    5. Michal Andrle, 2013. "What Is in Your Output Gap? Unified Framework & Decomposition into Observables," IMF Working Papers 2013/105, International Monetary Fund.
    6. Dimitrios Thomakos & Hossein Hassani & Kerry Patterson, 2013. "Optimal Linear Filtering, Smoothing and Trend Extraction for the m-th Differences of a Unit Root Process: A Singular Spectrum Analysis Approach," Economics Discussion Papers em-dp2013-04, Department of Economics, University of Reading.
    7. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.

    More about this item

    Keywords

    business cycles; mechanical filters; spectral analysis; bootstrap;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    Statistics

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