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  • Search: subject:"total variation denoising"
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Subject
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Lasso regression 3 Estimation theory 2 Hodrick–Prescott filtering 2 Regression analysis 2 Regressionsanalyse 2 Schätztheorie 2 Time series analysis 2 Whittaker–Henderson method of graduation 2 Zeitreihenanalyse 2 basis pursuit denoising 2 total variation denoising 2 ℓ1 trend filtering 2 Common trend 1 Hodrick-Prescott filtering 1 Reduced rank regression 1 Total variation denoising 1 l1 trend filtering 1
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Free 3
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2 Article 1
Language
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English 3
Author
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Yamada, Hiroshi 3 Du, Ruixue 2 Bao, Ruoyi 1
Published in...
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Computational economics 1 Econometrics 1 Econometrics : open access journal 1
Source
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ECONIS (ZBW) 2 EconStor 1
Showing 1 - 3 of 3
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L1 common trend filtering
Yamada, Hiroshi; Bao, Ruoyi - In: Computational economics 59 (2022) 3, pp. 1005-1025
Persistent link: https://www.econbiz.de/10013169212
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Some results on ℓ1 polynomial trend filtering
Yamada, Hiroshi; Du, Ruixue - In: Econometrics 6 (2018) 3, pp. 1-10
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...
Persistent link: https://www.econbiz.de/10011995228
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Some results on ℓ1 polynomial trend filtering
Yamada, Hiroshi; Du, Ruixue - In: Econometrics : open access journal 6 (2018) 3, pp. 1-10
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...
Persistent link: https://www.econbiz.de/10011887661
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