Artikel
Some results on ℓ1 polynomial trend filtering
ℓ1 polynomial trend filtering, which is a filtering method described as an ℓ1-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.
- Language
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Englisch
- Bibliographic citation
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Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 6 ; Year: 2018 ; Issue: 3 ; Pages: 1-10 ; Basel: MDPI
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Subject
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ℓ1 trend filtering
Hodrick–Prescott filtering
Whittaker–Henderson method of graduation
Lasso regression
basis pursuit denoising
total variation denoising
- Event
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Geistige Schöpfung
- (who)
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Yamada, Hiroshi
Du, Ruixue
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2018
- DOI
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doi:10.3390/econometrics6030033
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
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Object type
- Artikel
Associated
- Yamada, Hiroshi
- Du, Ruixue
- MDPI
Time of origin
- 2018
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