Time Series: Modeling, Computation, and Inference

1st Edition

Raquel Prado, Mike West

Chapman and Hall/CRC
Published May 21, 2010
Textbook - 368 Pages - 83 B/W Illustrations
ISBN 9781420093360 - CAT# C9336
Series: Chapman & Hall/CRC Texts in Statistical Science

For Instructors Request Inspection Copy

was $125.00

USD$100.00

SAVE ~$25.00

Add to Wish List
FREE Standard Shipping!

Summary

Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers.

The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites.

Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.

Instructors

We provide complimentary e-inspection copies of primary textbooks to instructors considering our books for course adoption.

Request an
e-inspection copy

Share this Title