Master thesis | Statistical Science for the Life and Behavioural Sciences (MSc)
open access
Online Linear Regression is a sequential variant of regression in which the data points arrive one by one. It is normally studied in the gametheoretic framework of Online Convex Optimization, which...Show moreOnline Linear Regression is a sequential variant of regression in which the data points arrive one by one. It is normally studied in the gametheoretic framework of Online Convex Optimization, which models the data as being generated by an adversary. In this framework, the standard statistical procedure of Online Ridge Regression is known to be essentially optimal. In Statistics, there is an improvement for Ridge Regression when the noise is not constant. This improvement is Weighted Ridge Regression, which relies on weighting the data by their variances. In this thesis, we will employ weighting in Online Ridge Regression to show that an improvement over Online Ridge Regression can be made. We furthermore explored the situation where weighting is disadvantageous, mathematically and experimentally using simulations. Finally we applied Online Weighted Ridge Regression to different real-world datasets and found that we also can improve Online Ridge Regression in practical situationsShow less
