James McMurray's Blog

Rust, Linux and other curiosities

The Expectation Maximisation (EM) Algorithm

In this post I will briefly introduce the EM algorithm with two simple examples. The EM algorithm uses an iterative approach to find the Maximum Likelihood estimate for a model with latent variables.

Note I will not provide a thorough coverage of the mathematics but rather focus on two examples of Gaussian Mixture Models.

Resources to learn Spanish

In this post I list some resources which have helped me to learn Spanish, I hope that they will help you too!

All of the listed resources are (mostly) free, except News In Slow Spanish (and the Latino version), and clearly the textbooks, TV series and films.

Introduction to Mendelian Randomization

Mendelian Randomization is an approach to test for a causal effect from observational data in the presence of certain confounding factors. It uses the measured variation of genes (of known function) to bound the causal effect of a modifiable exposure (environment) on a phenotype (disease). The fundamental idea is that the genotypes are randomly assigned (due to recombination in meiosis under certain assumptions), and this allows them to be used as an instrumental variable.

First Post

I've started this blog to save resources which have helped me in learning languages, concepts in statistics, and anything else which I think might help others too.