Mixing with Julia
We have such a mixture now, such a fusion of different genres. Ryszard Kapuscinski A while ago , I wrote a small app in Julia . In some of my other work, I needed to look at some data that could be modeled as being drawn from a mixture of probability distributions. There are many packages available in R and Python for analyzing mixture models . However, since version 1.1 of Julia was released recently, I decided to renew my acquaintance with the language by using it to build a simple mixture of normal (Gaussian) distributions. Although Julia provides methods for handling mixture models, I wanted to build my own routine for analysis to get some practice with Julia. Finite Mixture Models A mixture model is a probabilistic distribution that combines a set of components to represent the overall distribution. That is, given a set of data ${\mathbf{X}} = \{ {{\mathbf{x}}_1},{{\mathbf{x}}_2}...{{\mathbf{x}}_n}\} $ where each ${{\mathbf{x}}_{\mathbf{i}}}$ is an ...