Functional Data Analysis (FDA) is an exciting area of statistics that has gained momentum over recent years, especially with the rise of big data and the availability of continuous-time or high-frequency data. If you’re just getting started, FDA might seem complex, but with the right resources, you can build a strong foundation and explore its many applications in areas such as finance, biology, and climatology.

In this article, I’ll guide you through some essential resources to help you embark on your FDA journey, offering recommendations based on different experience levels and applications.

I. Start with the Classic: Ramsay and Silverman’s Book

James Ramsay and Bernard Silverman’s Functional Data Analysis is often seen as the go-to introduction to the field [1]. It breaks down complex concepts like functional principal component analysis, smoothing techniques, and functional regression in a way that’s both accessible and deeply insightful. The authors draw on real-world datasets to demonstrate the power of functional data methods, ranging from biomechanics to climatology.

Sources

1. 
   Ramsay, J. O. and Silverman, B. W. (2005). Functional Data Analysis. Springer Series in Statistics. Springer New York.[↩]