Design Matrix for Regression Explained
Recently I was asked about the design matrix (or model matrix) for a regression model and why it is important. […]
Introduction to Outlier Detection
Outlier detection and treatment is an important part of data analysis and one of the first things you should do […]
UTA100 2018: Race report
This was my first UTA100. A race I’ve long wanted to do. It’s an amazing event, the atmosphere is exhilarating […]
Agile Methodology for Data Science Projects
Agile project management methodology is a powerful framework when businesses are faced with uncertainty, rigid time frames and budget constraints. […]
Singular Value Decomposition: Image Compression
Singular value decomposition (SVD) is a matrix factorisation technique. It is a method to factorise any given matrix into 3 […]
What is the Bayes Factor anyway?
The Bayes Factor is a quantitative measure of much evidence there is for hypothesis A relative to hypothesis B given […]
Forecasting Air Pollution Levels with State Space Models
Recently I was looking at a Kaggle dataset on air quality and the relationships between the concentrations of contaminants and […]
State Space Models for Time Series Analysis and the dlm package
State space modelling is a popular technique for forecasting and smoothing time series data. There are two main components which […]
Classifying with Discrete Time Markov Chains
Discrete Time Markov Chain A discrete time markov chain is a stochastic model describing a sequence of observed events. The […]
Metropolis-Hastings Algorithm from Scratch
Metropolis Algorithm The Metropolis algorithm is a common acceptance/rejection algorithm for sampling from target distributions and a key tool for […]
