Description: Functional data analysis is a branch of statistics that focuses on the study of data that can be represented as functions. Unlike traditional data presented in the form of vectors or matrices, functional data is continuous and can be described through curves, surfaces, or any form that represents a phenomenon over time or space. This methodology allows for capturing the variability and inherent structure of the data, providing a richer and more detailed view. The main characteristics of functional data analysis include the ability to handle high-dimensional data, the use of smoothing techniques to improve function estimation, and the application of statistical models that consider the correlation between observations. Its relevance lies in its application across various disciplines, such as biomedicine, economics, and engineering, where the phenomena under study are intrinsically functional. By enabling a deeper and more meaningful analysis, functional data analysis has become an essential tool for researchers and professionals seeking to understand complex patterns in their data.
