Nonlinear Time Series Analysis with R

Product Details:

• Author: Ray Huffaker
• Publisher: Oxford Univ Pr on Demand
• ISBN: 9780198808251
• Pages: 372
• Cover: Paperback
• Language: English
• Dimensions: 9.6 x 6.7 x 0.8 inches

About the Book:

Nonlinear Time Series Analysis with R provides a practical and in-depth guide for professionals and graduate students to tackle the complexities of time series data. This book equips readers with the empirical tools needed to determine whether the fluctuations and randomness observed in data are driven by random external forces or by inherent deterministic dynamic processes.

Time series data, commonly characterized by high fluctuation and randomness, are often interpreted as being influenced by external, unpredictable shocks. However, the emerging field of nonlinear dynamics offers a paradigm shift: complex patterns and behaviors can emerge from seemingly simple, deterministic models. Nonlinear Time Series Analysis (NLTS) helps practitioners investigate whether observed patterns are likely the result of stochastic or deterministic forces.

Targeted at non-mathematicians, the book is designed to empower professionals and students, especially in engineering, biophysics, and the social sciences, to apply NLTS methods effectively. The author focuses on making nonlinear dynamics accessible, with hands-on computer experiments using R code to demonstrate NLTS techniques. These practical experiments guide readers through the methods while helping them understand the theoretical concepts behind the analysis.

By explaining the R code in detail, the book ensures that readers can tailor the methods to their own work, making it a valuable resource for anyone looking to incorporate nonlinear time series analysis into their research or coursework. Additionally, the book offers a step-by-step framework, based on best practices from the literature, to apply NLTS to real-world data diagnostics, making it an essential tool for modern data-driven scientific investigation.

Whether you're new to nonlinear dynamics or looking to deepen your understanding of the field, Nonlinear Time Series Analysis with R provides the essential tools and knowledge needed to become proficient in this exciting and rapidly advancing area of study.