Elements of Nonlinear Time Series Analysis and Forecasting / by Jan G. De Gooijer.

Format:

Book

Author/Creator:

De Gooijer, Jan G., Author.

Series:

Springer Series in Statistics, 2197-568X

Language:

English

Subjects (All):

Statistics.

Biometry.

Nonlinear optics.

Statistical Theory and Methods.

Biostatistics.

Statistics in Business, Management, Economics, Finance, Insurance.

Nonlinear Optics.

Local Subjects:

Statistical Theory and Methods.

Biostatistics.

Statistics in Business, Management, Economics, Finance, Insurance.

Nonlinear Optics.

Physical Description:

1 online resource (XXI, 618 p. 95 illus. in color.)

Edition:

1st ed. 2017.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2017.

Summary:

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual. .

Contents:

Introduction and Some Basic Concepts

Classic Nonlinear Models

Probabilistic Properties

Frequency-Domain Tests

Time-Domain Linearity Tests

Model Estimation, Selection and Checking

Tests for Serial Independence

Time-Reversibility

Semi- and Nonparametric Forecasting

Forecasting Vector Parametric Models and Methods

Vector Semi- and Nonparametric Methods. .

Notes:

Includes index.

ISBN:

9783319432526

3319432524