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pro vyhledávání: '"Bergersen, Linn Cecilie"'
We consider the problems of variable selection and estimation in nonparametric additive regression models for high-dimensional data. In recent years, several methods have been proposed to model nonlinear relationships when the number of covariates ex
Externí odkaz:
http://arxiv.org/abs/1310.1282
Autor:
Bergersen, Linn Cecilie, Ahmed, Ismaïl, Frigessi, Arnoldo, Glad, Ingrid K., Richardson, Sylvia
We propose a new approach to safe variable preselection in high-dimensional penalized regression, such as the lasso. Preselection - to start with a manageable set of covariates - has often been implemented without clear appreciation of its potential
Externí odkaz:
http://arxiv.org/abs/1210.0380
Publikováno v:
In Computational Statistics and Data Analysis September 2014 77:336-351
Autor:
Bergersen, Linn Cecilie
Publikováno v:
Bergersen, Linn Cecilie. Data Integration in Penalized Regression Models. Masteroppgave, University of Oslo, 2009
Externí odkaz:
http://hdl.handle.net/10852/10831
https://www.duo.uio.no/bitstream/handle/10852/10831/1/Masteroppgave.pdf
https://www.duo.uio.no/bitstream/handle/10852/10831/1/Masteroppgave.pdf
Autor:
Bergersen, Linn Cecilie, Ahmed, Ismaïl, Frigessi, Arnoldo, Glad, Ingrid K., Richardson, Sylvia
Publikováno v:
Statistical Analysis for High-Dimensional Data; 2016, p37-66, 30p
Akademický článek
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