# Posts

My thoughts and ideas

• ## Decomposition of Autoregressive Models

We discuss the decomposition of AR models into components, and how eigenvalues are involved (because they always are).

• ## Markov Chain Monte Carlo

Markov Chain Monte Carlo is a tool for sampling otherwise intractible distributions. In this post, we’ll go through some descriptions, reasoning, and examples therein.

• ## Linear Regression -- The Basics

Linear Regression is the bedrock of Machine Learning. We cover the basics therein, some theory involved, and give some relevant examples.

• ## Probability -- A Measure Theoretic Approach

We cover probability from a measure theoretic approach