Some Results on ℓ1 Polynomial Trend Filtering
Graduate School of Social Sciences, Hiroshima University, 1-2-1 Kagamiyama, Higashi-Hiroshima 739-8525, Japan
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Received: 22 May 2018 / Revised: 30 June 2018 / Accepted: 4 July 2018 / Published: 10 July 2018
(This article belongs to the Special Issue Filtering
polynomial trend filtering, which is a filtering method described as an
-norm penalized least-squares problem, is promising because it enables the estimation of a piecewise polynomial trend in a univariate economic time series without prespecifying the number and location of knots. This paper shows some theoretical results on the filtering, one of which is that a small modification of the filtering provides not only identical trend estimates as the filtering but also extrapolations of the trend beyond both sample limits.
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MDPI and ACS Style
Yamada, H.; Du, R. Some Results on ℓ1 Polynomial Trend Filtering. Econometrics 2018, 6, 33.
Yamada H, Du R. Some Results on ℓ1 Polynomial Trend Filtering. Econometrics. 2018; 6(3):33.
Yamada, Hiroshi; Du, Ruixue. 2018. "Some Results on ℓ1 Polynomial Trend Filtering." Econometrics 6, no. 3: 33.
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