Dynamic Time Series Models using R-INLA: An Applied Perspective

Ravishanker, Nalini; Raman, Balaji; Soyer, Refik

ISBN 10: 036765427X / ISBN 13: 9780367654276

Published by Chapman and Hall/CRC, 2022

In. Seller Inventory # ria9780367654276_new

Synopsis:

Dynamic Time Series Models using R-INLA: An Applied Perspective is the outcome of a joint effort to systematically describe the use of R-INLA for analysing time series and showcasing the code and description by several examples. This book introduces the underpinnings of R-INLA and the tools needed for modelling different types of time series using an approximate Bayesian framework.

The book is an ideal reference for statisticians and scientists who work with time series data. It provides an excellent resource for teaching a course on Bayesian analysis using state space models for time series.

Key Features:

• Introduction and overview of R-INLA for time series analysis.
• Gaussian and non-Gaussian state space models for time series.
• State space models for time series with exogenous predictors.
• Hierarchical models for a potentially large set of time series.
• Dynamic modelling of stochastic volatility and spatio-temporal dependence.

About the Author:

Nalini Ravishanker is a professor in the Department of Statistics at the University of Connecticut, Storrs, USA.

Balaji Raman is a statistician at Cogitaas AVA, Mumbai, India.

Refik Soyer is a professor in the Department of Decision Sciences at The George Washington University, Washington D.C., USA.

Bibliographic Details

Title: Dynamic Time Series Models using R-INLA: An ...
Publisher: Chapman and Hall/CRC
Publication Date: 2022
Binding: Hardcover
Condition: New