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Mathematical Foundations of Time Series Analysis : A Concise Introduction / by Jan Beran.
Author
Beran, Jan
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Format
Book
Language
English
Εdition
1st ed. 2017.
Published/Created
Cham : Springer International Publishing : Imprint: Springer, 2017.
Description
1 online resource (309 pages)
Availability
Available Online
Springer Nature - Springer Mathematics and Statistics eBooks 2017 English International
Details
Subject(s)
Statistics .
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Econometrics
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Probabilities
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Summary note
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.
Contents
Introduction
Typical assumptions
Defining probability measure for time series
Spectral representation of univariate time series
Spectral representation of real valued vector time series
Univariate ARMA processes
Generalized autoregressive processes
Prediction
Inference for μ, γ and F
Parametric estimation
References.
Show 8 more Contents items
ISBN
3-319-74380-5
Doi
10.1007/978-3-319-74380-6
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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