Nalini Ravishanker, Balaji Raman, Refik Soyer

Dynamic Time Series Models using R-INLA (eBook, ePUB)

An Applied Perspective

• Format: ePub

Produktbeschreibung

This Book 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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 296
• Erscheinungstermin: 10. August 2022
• Englisch
• ISBN-13: 9781000622874
• Artikelnr.: 64308962

Autorenporträt

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.

Inhaltsangabe

Preface. 1. Bayesian Analysis. 2. A Review of INLA. 3. Modeling Univariate
Time Series. 4. More Topics on DLMs with R-INLA. 5. Modeling Time Series
with Exogenous Predictors. 6. Structural Time Series Decomposition using
R-INLA. 7. Hierarchical DLM. 8. INLA for Multivariate Dynamic Models. 9.
Modeling Binary Time Series. 10. Modeling Count Time Series. 11. Modeling
Stochastic Volatility. 12. Comparison of R-INLA to Other Bayesian
Alternatives. 13. Resources for the User.