Local polynomial regression

Local polynomial regression is a statistical method used to estimate the relationship between variables in a dataset by fitting simple polynomial models (like lines or curves) to small, nearby regions of the data. Instead of applying one global model to all data points, it focuses on localized areas, capturing patterns that may change across the data. This approach provides smooth, flexible fits that adapt to local trends, making it useful for understanding complex, non-linear relationships while maintaining stability and interpretability in the estimates.