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Mathematical Foundations of Time Series Analysis: A Concise...

Mathematical Foundations of Time Series Analysis: A Concise Introduction

Jan Beran
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Main subject categories: • Time series • Time series analysis • Stochastic processes • Statistical inference

Mathematics Subject Classification (2010): • 62Mxx Inference from stochastic processes • 62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.

“Beran (Univ. of Konstanz, Germany) presents the mathematical foundations of time series analysis at a level suitable for advanced graduate students and researchers in statistics. The presentation is extremely concise … . the book gives definitions, theorems, and proofs, along with a few exercises and solutions. … it may be useful to graduate students and researchers as a reference.” (B. Borchers, Choice, Vol. 56 (03), November, 2018)​

年:
2017
出版:
1
出版社:
Springer, Springer International Publishing AG, Springer Nature
语言:
english
页:
309
ISBN 10:
3030089754
ISBN 13:
9783030089757
文件:
PDF, 1.18 MB
IPFS:
CID , CID Blake2b
english, 2017
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