 Название: Mathematical Foundations of Time Series Analysis
Автор: Jan Beran
Издательство: Springer International Publishing
Год: 2017
ISBN: 9783319743806
Формат: epub, pdf
Страниц: IX, 307
Размер: 10,1 mb
Язык: English
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.
Introduction
Beran, Jan
Pages 1-4
Typical Assumptions
Beran, Jan
Pages 5-68
Defining Probability Measures for Time Series
Beran, Jan
Pages 69-100
Spectral Representation of Univariate Time Series
Beran, Jan
Pages 101-135
Spectral Representation of Real Valued Vector Time Series
Beran, Jan
Pages 137-159
Univariate ARMA Processes
Beran, Jan
Pages 161-202
Generalized Autoregressive Processes
Beran, Jan
Pages 203-222
Prediction
Beran, Jan
Pages 223-239
Inference for ?, ? and F
Beran, Jan
Pages 241-280
Parametric Estimation
Beran, Jan
Pages 281-291
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Mathematical Foundations of Time Series Analysis 
