Major Papers


A recent issue in statistical analysis is modelling data when the effect variable

changes at different locations. This can be difficult to accomplish when the dimensions

of the covariates are very high, and when the domain of the varying coefficient

functions of predictors are not necessarily regular. This research paper will investigate

a method to overcome these challenges by approximating the varying coefficient

functions using bivariate splines. We do this by splitting the domain of the varying

coefficient functions into a number of triangles, and build the bivariate spline functions

based on this triangulation. This major paper will outline detailed theoretical results

of this method, and provide simulation studies to demonstrate the efficiency of this

approach. Finally, to illustrate the application of this method, we analyze heart

disease dataset where the given covariates are in spatially varying form.

Primary Advisor

Dr. Sévérien Nkurunziza

Program Reader

Dr. Mohamed Belalia

Degree Name

Master of Science


Mathematics and Statistics

Document Type

Major Research Paper

Convocation Year