Dynamic time series models using R-INLA : an applied perspective /
"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 ne...
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Main Authors: | |
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Group Author: | ; |
Published: |
CRC Press, Taylor & Francis Group,
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Publisher Address: | Boca Raton, FL : |
Publication Dates: | 2023. |
Literature type: | Book |
Language: | English |
Edition: | First edition. |
Subjects: | |
Summary: |
"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"-- |
Carrier Form: | xiii, 282 pages : illustrations (some color) ; 26 cm |
Bibliography: | Includes bibliographical references (pages 273-279) and index. |
ISBN: |
9780367654276 036765427X 9780367680626 0367680629 |
Index Number: | QA280 |
CLC: | O211.61 |
Call Number: | O211.61/R256 |
Contents: | Bayesian analysis -- A review of INLA -- Modeling univariate time series -- More topics on DLMs with R-INLA -- Modeling time series with exogenous predictors -- Structural time series decomposition using R-INLA -- Hierarchical DLM -- INLA for multivariate dynamic models -- Modeling binary time series -- Modeling count time series -- Modeling stochastic volatility -- Comparison of R-INLA to other Bayesian alternatives -- Resources for the user. |