03854nam a22005415i 4500
978-3-319-28599-3
DE-He213
20181204134229.0
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160509s2016 gw | s |||| 0|eng d
9783319285993
978-3-319-28599-3
10.1007/978-3-319-28599-3
doi
ISI Library, Kolkata
QA276-280
PBT
bicssc
MAT029000
bisacsh
PBT
thema
519.5
23
Gómez, Víctor.
author.
aut
http://id.loc.gov/vocabulary/relators/aut
Multivariate Time Series With Linear State Space Structure
[electronic resource] /
by Víctor Gómez.
Cham :
Springer International Publishing :
Imprint: Springer,
2016.
XVII, 541 p.
online resource.
text
txt
rdacontent
computer
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rdamedia
online resource
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rdacarrier
text file
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Preface -- Computer Software -- Orthogonal Projection -- Linear Models -- Stationarity and Linear Time Series Models -- The State Space Model -- Time Invariant State Space Models -- Time Invariant State Space Models With Inputs -- Wiener–Kolmogorov Filtering and Smoothing -- SSMMATLAB -- Bibliography -- Author Index -- Subject Index.
This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.
Mathematical statistics.
Distribution (Probability theory.
Statistics.
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http://scigraph.springernature.com/things/product-market-codes/S12008
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http://scigraph.springernature.com/things/product-market-codes/M27004
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
http://scigraph.springernature.com/things/product-market-codes/S17020
Econometrics.
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Statistics for Business/Economics/Mathematical Finance/Insurance.
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Springer eBooks
Printed edition:
9783319285986
Printed edition:
9783319286006
Printed edition:
9783319803852
https://doi.org/10.1007/978-3-319-28599-3
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Mathematics and Statistics (Springer-11649)
426565
426565