by Aditya Pandya
This is the Python script for performing fast Bayesian linear regression.
It takes in the x and y data along with their errors and gives best-fit results such as slope, intercept, intrinsic scatter, and standard deviation values.
It requires the use of 2 Python packages: numpy and numba
Install numba using "$ pip install numba" in the terminal.
For more documentation, visit: https://numba.pydata.org/numba-doc/latest/index.html
Along with the Python script, there is a jupyter notebook file which shows how to use the script with an example along with the basics of Bayesian linear regression.
Here is the flowchart of the algorithm used for Bayesian linear regression:
