Univariate Tests for Time Series Models

1. Auflage 1994
ISBN: 978-0-8039-4991-1
Verlag: Sage Publications, Inc.

Buch, Englisch, Band 99, 104 Seiten, Format (B × H): 140 mm x 216 mm, Gewicht: 143 g

Reihe: Quantitative Applications in the Social Sciences

Taking a sequential approach to time-series model building, this book explores how to test for stationarity, normality, independence, linearity, model order, and properties of the residual process. The authors clearly define each testing procedure and offer examples to illustrate each concept. The authors also provide advice on how to perform the tests using different software packages. "This provides a nice roadmap for those doing time series analysis, and the authors should be applauded for this. Their approach is straightforward and logical and I believe will be useful many practicing statisticians." --Technometrics

Autoren/Hrsg.

Cromwell, Jeff B.

Cromwell, Jeffrey B.

Labys, Walter C.

Terraza, Michel

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Gesellschaftstheorie

Inhaltsverzeichnis

Introduction
Testing for Stationarity
Testing for Normality
Testing for Independence
Testing for Linear or Nonlinear Dependence
Linear Model Specification
Nonlinear Model Specification
Testing for Model Order
Testing for Residual Process
Computational Methods for Performing the Tests

Über Autor(innen)

Terraza, Michel
Michel Terraza is a science Professor of economics at Montpellier I University. He applied this decomposed measure when studying the wages inequalities in the Languedoc-Roussillon region (see the bibliography). He did it in collaboration with Françoise Seyte (Associate Professor) and Stéphane Mussard (Assistant Professor).

Cromwell, Jeffrey B.
Dr. Jeff B. Cromwell is a graduate of West Virginia University with research interests in computational statistics, econometrics and time series analysis.