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Bayesian Inference of State Space Models

Kalman Filtering and Beyond
BuchKartoniert, Paperback
495 Seiten
Englisch
Springererschienen am13.11.20221st ed. 2021
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.mehr
Verfügbare Formate
BuchGebunden
EUR139,09
BuchKartoniert, Paperback
EUR85,59
E-BookPDF1 - PDF WatermarkE-Book
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Produkt

KlappentextBayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
Details
ISBN/GTIN978-3-030-76126-4
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2022
Erscheinungsdatum13.11.2022
Auflage1st ed. 2021
ReiheSpringer Texts in Statistics
Seiten495 Seiten
SpracheEnglisch
IllustrationenXV, 495 p. 87 illus., 33 illus. in color.
Artikel-Nr.51198004

Inhalt/Kritik

Inhaltsverzeichnis
1 State Space Models.- 2 Matrix Algebra, Probability and Statistics.- 3 The Kalman Filter.- 4 Model Specification and Model Performance.- 5 Multivariate State Space Models.- 6 Non-linear and non-Gaussian State Space Models.- 7 The State Space Model in Finance.- 8 Dynamic Systems and Control.- References.- Index.mehr
Kritik
"The idea of this book is to bring together the mentioned models and make them available to a broad audience. The book is written from a statistician's perspective. It uses a number of data sets from a wide range of disciplines. ... It is aimed at students at the higher end of undergraduate or graduate level but also at scientists for self-study." (Wolfgang Näther, zbMATH 1480.62003, 2022)mehr

Schlagworte

Autor

Kostas Triantafyllopoulos is a Senior Lecturer at the School of Mathematics and Statistics of the University of Sheffield. He holds a PhD in Statistics from the University of Warwick and prior to Sheffield worked as a Research Associate at the University of Bristol and as a Lecturer at the University of Newcastle upon Tyne. His research interests include Bayesian inference of time series models and statistical process control. He has published widely and is involved in research grants including the Nuffield Foundation, the NHS and the Engineering and Physical Sciences Research Council (UK). He has wide teaching experience in statistics and has supervised a number of doctoral students and postdoctoral fellows.
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Triantafyllopoulos, Kostas