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Improving Lasso for model selection and prediction

Published:2021-07 Issue: Volume: Page:
ISSN:0303-6898
Container-title:Scandinavian Journal of Statistics
language:en
Short-container-title:Scand J Statist

Author:

Pokarowski Piotr¹,Rejchel Wojciech²^ORCID,Sołtys Agnieszka¹,Frej Michał¹,Mielniczuk Jan³⁴

Affiliation:

1. Institute of Applied Mathematics and Mechanics University of Warsaw Warsaw Poland

2. Faculty of Mathematics and Computer Science Nicolaus Copernicus University Toruń Poland

3. Institute of Computer Sciences Polish Academy of Sciences Warsaw Poland

4. Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw Poland

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/sjos.12546

Reference40 articles.

1. Convexity, Classification, and Risk Bounds

2. Simultaneous analysis of Lasso and Dantzig selector

3. Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection

4. Statistics for High-Dimensional Data

5. Least angle regression

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1. Structure learning for continuous time Bayesian networks via penalized likelihood;Scandinavian Journal of Statistics;2024-08-20

2. Construction and Analysis for the Optimal Supersaturated Designs with a Large Number of Inert Factors;Axioms;2024-03-08

3. Building a cross-border e-commerce talent training platform based on logistic regression model;The Journal of High Technology Management Research;2023-11

4. DMRnet: Delete or Merge Regressors Algorithms for Linear and Logistic Model Selection and High-Dimensional Data;CRAN: Contributed Packages;2017-09-05

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