Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist

© Thomas Mailund 2022

T. MailundBeginning Data Science in R 4https://doi.org/10.1007/978-1-4842-8155-0_17

17. Project 2: Bayesian Linear Regression

Thomas Mailund¹  

(1)

Aarhus, Denmark

 

The project for this chapter is building an R package for Bayesian linear regression. The model we will work with is somewhat a toy example of what we could imagine we could build an R package for, and the goal is not to develop all the bells and whistles of Bayesian linear regression. We will just build enough to see the various aspects that go into building a real R package.

Bayesian Linear Regression

In linear regression, we assume that we have predictor variables x and target variables y where y = w₀ + w₁x + ϵ where ϵ ∼ N(0, σ²). That is, we have a line with intercept ...