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A New Method for Specifying the Tuning Parameter of ℓ1 Trend Filtering

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  • Yamada Hiroshi

    (Hiroshima University, Graduate School of Social Sciences, 1-2-1 Kagamiyama, Higashi-Hiroshima 739-8525, Japan)

Abstract

Because Hodrick–Prescott (HP) filtering and ℓ1 trend filtering are expressed as penalized least squares problem, both of them require the specification of their tuning parameter. For HP filtering, we have accumulated knowledge for selecting the value of its tuning parameter. However, we do not have similar knowledge for ℓ1 trend filtering. This paper presents a new method for specifying the tuning parameter of ℓ1 trend filtering so that the sum of squared residuals of HP filtering and that of ℓ1 trend filtering may be equivalent.

Suggested Citation

  • Yamada Hiroshi, 2018. "A New Method for Specifying the Tuning Parameter of ℓ1 Trend Filtering," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-8, September.
    • Handle: RePEc:bpj:sndecm:v:22:y:2018:i:4:p:8:n:3
    DOI: 10.1515/snde-2016-0073
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    Citations

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    Cited by:

    1. Hiroshi Yamada & Ruixue Du, 2018. "Some Results on ℓ 1 Polynomial Trend Filtering," Econometrics, MDPI, vol. 6(3), pages 1-10, July.

    More about this item

    Keywords

    constrained minimization; Hodrick–Prescott filtering; ℓ1 trend filtering; tuning parameter;
    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

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