October 2015
Beginner to intermediate
168 pages
4h 11m
English
In the previous chapter, we covered the theory of Bayesian linear regression in some detail. In this chapter, we will take a sample problem and illustrate how it can be applied to practical situations. For this purpose, we will use the generalized linear model (GLM) packages in R. Firstly, we will give a brief introduction to the concept of GLM to the readers.
Recall that in linear regression, we assume the following functional form between the dependent variable Y and independent variable X:
Here, is a set of basis functions and is the parameter vector. Usually, it is assumed that ...
Read now
Unlock full access