Connection Between OLS and Theil-Sen Estimators
A deep dive into the relationship between OLS and Theil-Sen estimators, revealing their connection through weighted averages and robust median-based slopes.
A deep dive into the relationship between OLS and Theil-Sen estimators, revealing their connection through weighted averages and robust median-based slopes.
Explore exchange rate models like Purchasing Power Parity (PPP) and Uncovered Interest Parity (UIP), key frameworks in global economics.
Explore how Finite Difference Methods and the Black-Scholes-Merton differential equation are used to solve option pricing problems numerically, with a focus on explicit and implicit schemes.
Discover how data science enhances supply chain optimization and industrial network analysis, leveraging techniques like predictive analytics, machine learning, and graph theory to optimize operations.
Linear Programming is the foundation of optimization in operations research. We explore its traditional methods, challenges in scaling large instances, and introduce PDLP, a scalable solver using first-order methods, designed for modern computational infrastructures.
Explore key metrics for evaluating classification and regression models.
Understand how decision tree algorithms split data and how pruning improves generalization.
Learn how to design robust data preprocessing pipelines that prepare raw data for modeling.
This article explores the use of K-means clustering in crime analysis, including practical implementation, case studies, and future directions.
A step-by-step guide to implementing Linear Regression from scratch using the Normal Equation method, complete with Python code and evaluation techniques.