Review of Statistical Learning for Big, Dependent Data.

The book review discusses "Statistical Learning for Big, Dependent Data" by Daniel Pen ˜ a and Ruey S. Tsay, published in 2021. The book covers approaches for analyzing data with temporal or geo-spatial dependencies, which are increasingly relevant due to the availability of vast data with less control over its properties. It includes chapters on time series modeling, extreme events analysis, clustering, machine learning, and spatio-temporal dependencies, making it a valuable resource for official statistics and rigorous statistical analysis. The text provides practical insights, examples, and exercises, along with R code for hands-on experience, making it accessible for researchers and practitioners in the field. [Extracted from the article]