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Linear regression in the Bayesian framework

Abstract : These notes aim at clarifying different strategies to perform linear regression from given dataset. Methods like the weighted and ordinary least squares, ridge regression or LASSO are proposed in the literature. The present article is my understanding of these methods which are, according to me, better unified in the Bayesian framework. The formulas to address linear regression with these methods are derived. The KIC for model selection is also derived in the end of the document.
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Contributor : Thierry Mara <>
Submitted on : Wednesday, August 7, 2019 - 10:47:56 PM
Last modification on : Thursday, July 1, 2021 - 3:04:42 AM
Long-term archiving on: : Thursday, January 9, 2020 - 6:43:26 PM


Notes on Bayesian Linear Regre...
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  • HAL Id : hal-02264944, version 1
  • ARXIV : 1908.03329



Thierry A. Mara. Linear regression in the Bayesian framework. 2019. ⟨hal-02264944⟩



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