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.
Document type :
Preprints, Working Papers, ...
Complete list of metadatas

Cited literature [9 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02264944
Contributor : Thierry Mara <>
Submitted on : Wednesday, August 7, 2019 - 10:47:56 PM
Last modification on : Saturday, August 10, 2019 - 1:24:05 AM

Files

Notes on Bayesian Linear Regre...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02264944, version 1
  • ARXIV : 1908.03329

Collections

Citation

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

Share

Metrics

Record views

7

Files downloads

14