Hands-On Time Series Analysis with R

Master modern time series forecasting in R using real datasets, applied models like ARIMA and Prophet, and advanced tools like LSTM for business-ready analysis Key Features Build a practical skills in time series forecasting using R from scratch Levereage traditional and deep learning models including ARIMA, Prophet, and LSTM Analyze and visualize real-world datasets to drive decisions and discover insights Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionHands-on Time Series Analysis with R, Second Edition, is a comprehensive, practical guide to understanding and applying time series analysis using R. Designed for professionals and students alike, the book will help you dissect time-ordered data, uncover trends, detect anomalies, and forecast future events. You’ll start with R fundamentals and data structures, progressing through time series visualization and decomposition,before covering classical forecasting methods like exponential smoothing and ARIMA. You’ll also familiarize yourself with cutting-edge forecasting techniques such as Bayesian modeling, TBATS, and multivariate forecasting. Building upon the extraordinary success of the first edition, this new edition explores the powerful Prophet library, neural networks, and LSTM models to handle complex forecasting challenges. Unlike other similar books, it uses real-world case studies from domains like e-commerce and supply chain make the content highly applicable, while self-assessment questions and step-by-step tutorials reinforce key concepts. By the end of this book, you’ll be able to confidently apply a wide array of forecasting methods to solve real-world business and research problems. What you will learn Work with time series data to uncover underlying patterns and trends…