图书名称：Multivariate Tests for Time Series Models
作者：Cromwell, Jeff B.
出版社：Sage Publications, Inc.
页数：98
出版时间：1994                          
语言：English
格式：pdf
内容：
Contents
Series Editor's Introduction v
1. Introduction 1
Relations Between Variables
Joint Stationarity
Covariance and Correlation
Time Series Tests and Model Building
2. Testing for Joint Stationarity, Normality, and Independence 9
Testing for Joint Stationarity
Fountis-Dickey Test
Transformations
Testing for Normality
Skewness and Kurtosis Test
Testing for Independence
Portmanteau Test
Pierce-Haugh Test
3. Testing for Cointegration 17
Cointegrating Regression Durbin-Watson (CRDW) Test
Dickey-Fuller (DF) Test
Augmented Dickey-Fuller (ADF) Test
Engle-Granger Tests
Johansen Test
Granger-Lee Test
4. Testing for Causality 32
Granger Causality Test
Sims Test
Geweke-Meese-Dent Test
Pierce-Haugh Test
Geweke Test
General Guidelines
5. Multivariate Linear Model Specification 56
Transfer Function Models (TF)
Vector Autoregressive Models (VAR)
Vector Moving Average Models (VMA)
Testing Decompositions and Impulse Functions
Bayesian Vector Autoregressive Models (BVAR)
Vector Autoregressive Moving Average Models (VARMA)
Error Correction Models (ECM)
State-Space Models
6. Multivariate Nonlinear Models 71
Feedforward Neural Networks
7. Model Order and Forecast Accuracy 73
Testing for Model Order
Testing for Forecast Accuracy
Accuracy of Individual Models
Nonparametric Tests
Comparative Accuracy Across Models
8. Computational Methods for Performing the Tests 84
Appendix: Statistical Tables 87
A.1 Critical Values for the Dickey-Fuller Test
A.2 Critical Values and Power of the Engle-Granger Test
A.3 Critical Values for the Engle-Yoo Cointegration Test
References 91
About the Authors 97