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.
ISBN
3-319-74380-5
Doi
10.1007/978-3-319-74380-6
Statement on responsible collection 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. Read more...