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Year of publication
Subject
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Big Data 3 Big data 3 Forecasting model 3 Google search data 3 Nowcasting 3 Prognoseverfahren 3 Search engine 3 Suchmaschine 3 ridge regularization 3 Bruttoinlandsprodukt 2 Gross domestic product 2 Ridge Regularization 2 Sure Independence Screening 2 Backfitting 1 Estimation theory 1 Impulse responses 1 Markov boundary 1 Nichtparametrische Schätzung 1 Nichtparametrisches Verfahren 1 Nonparametric estimation 1 Nonparametric statistics 1 Regression analysis 1 Regressionsanalyse 1 Ridge regularization 1 Schätztheorie 1 Statistical error 1 Statistischer Fehler 1 Targeted preselection 1 classical measurement error 1 inference 1 linear models 1 nonparametric additive regression 1 series estimation 1 vector autoregression 1
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Online availability
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Free 4 Undetermined 2 CC license 1
Type of publication
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Article 4 Book / Working Paper 2
Type of publication (narrower categories)
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Arbeitspapier 2 Article in journal 2 Aufsatz in Zeitschrift 2 Graue Literatur 2 Non-commercial literature 2 Working Paper 2 Article 1 research-article 1
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Language
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English 6
Author
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Ferrara, Laurent 3 Simoni, Anna 3 Ballarin, Giovanni 1 Dong, Hao 1 Otsu, Taisuke 1 Strobl, Eric V. 1 Taylor, Luke 1 Visweswaran, Shyam 1
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Published in...
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Document de travail 1 Econometric reviews 1 Journal of Causal Inference 1 Journal of Time Series Analysis 1 Journal of business & economic statistics : JBES ; a publication of the American Statistical Association 1 Série des documents de travail 1
Source
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ECONIS (ZBW) 4 EconStor 1 Other ZBW resources 1
Showing 1 - 6 of 6
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When are Google data useful to nowcast GDP? : an approach via preselection and shrinkage
Ferrara, Laurent; Simoni, Anna - In: Journal of business & economic statistics : JBES ; a … 41 (2023) 4, pp. 1188-1202
Persistent link: https://www.econbiz.de/10014448601
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Ridge regularized estimation of VAR models for inference
Ballarin, Giovanni - In: Journal of Time Series Analysis 46 (2024) 2, pp. 235-257
Ridge regression is a popular method for dense least squares regularization. In this article, ridge regression is studied in the context of VAR model estimation and inference. The implications of anisotropic penalization are discussed, and a comparison is made with Bayesian ridge‐type...
Persistent link: https://www.econbiz.de/10015410516
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Nonparametric estimation of additive models with errors-in-variables
Dong, Hao; Otsu, Taisuke; Taylor, Luke - In: Econometric reviews 41 (2022) 10, pp. 1164-1204
Persistent link: https://www.econbiz.de/10013490701
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When are Google data useful to nowcast GDP? : an approach via preselection and shrinkage
Ferrara, Laurent; Simoni, Anna - 2020
Persistent link: https://www.econbiz.de/10012242240
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When are Google data useful to nowcast GDP? : an approach via pre-selection and shrinkage
Ferrara, Laurent; Simoni, Anna - 2019
Persistent link: https://www.econbiz.de/10012237280
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Markov Boundary Discovery with Ridge Regularized Linear Models
Strobl, Eric V.; Visweswaran, Shyam - In: Journal of Causal Inference 4 (2016) 1, pp. 31-48
Abstract Ridge regularized linear models (RRLMs), such as ridge regression and the SVM, are a popular group of methods that are used in conjunction with coefficient hypothesis testing to discover explanatory variables with a significant multivariate association to a response. However, many...
Persistent link: https://www.econbiz.de/10014610828
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