Towards an interdisciplinary research path: Discrete Mathematics and Statistical Inference
My research explores the intersection of discrete mathematics and statistics, with a focus on high-dimensional inference. I am particularly interested in how discrete structures, such as graphs, logic, and combinatorics, can inform and improve statistical modelling, especially in areas like model selection and sparse learning.
A strong foundation in Discrete Mathematics is invaluable in this context. Two texts that have influenced my perspective are:
Discrete Mathematics with Applications by Susanna S. Epp.
Discrete Mathematics and Its Applications by Kenneth H. Rosen.
In this section, I share a collection of MATLAB functions that range from introductory to more advanced implementations. These algorithms are inspired by examples from the books mentioned above and are designed to support both learning and exploration. I will continue updating this repository with functions and algorithmic ideas that are relevant to my research or pedagogically useful for others. All interpretations and potential errors are my own.
Simple algorithms for beginners
if-else: link
while-loop: link
for-loop: link
Division algorithm: link
Euclidean algorithm: link
Decimal to binary conversion using division algorithm: link
Finding the maximum element in a finite sequence: link
A little more advanced algorithms
The bubble sort algorithm with time complexity \Theta(n^2) : link
Linear search algorithm with time complexity \Theta(n): link
Binary search algorithm: link
Kruskal's algorithm with undirected graph that produces a minimum spanning tree: Coming soon