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Tutorial 4: Autoregressive Models

Difficulty level

The goal of this tutorial is to use the modeling tools and intuitions developed in the previous few tutorials and use them to fit data. The concept is to flip the previous tutorial -- instead of generating synthetic data points from a known underlying process, what if we are given data points measured in time and have to learn the underlying process?

This tutorial is in two sections:

  • Section 1 walks through using regression of data to solve for the coefficient of an OU process from Tutorial 3.
  • Section 2 generalizes this auto-regression framework to high-order autoregressive models, and we will try to fit data from monkeys at typewriters.
Topics covered in this lesson
  • Fitting data to the OU process
  • Higher order autoregressive models

Experience with Python Programming Language

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