Description

"Bayesian Analysis for Time Series Models Detecting Shift Points and Outliers" by R. Chinnadurai provides an in-depth exploration of Bayesian analysis techniques for identifying and analyzing shift points and outliers in time series data. The book offers a comprehensive overview of Bayesian statistics, as well as the practical application of these techniques in real-world scenarios. With a focus on shift points and outliers, readers will gain a thorough understanding of the impact of these factors on time series data analysis, and the importance of detecting and analyzing these effects.

The book covers a wide range of topics, including model selection, prior specification, inference, and diagnostic tools, as well as case studies and examples demonstrating the application of Bayesian analysis to time series data. With clear explanations and a practical approach, this book is an essential resource for anyone seeking to understand and apply Bayesian analysis techniques to time series data.

Whether you're a student, researcher, or practitioner in the fields of statistics, economics, finance, or engineering, "Bayesian Analysis for Time Series Models Detecting Shift Points and Outliers" is a valuable resource for understanding and applying Bayesian analysis techniques to time series data.