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Which time series test should researchers choose to best describe the interactions among a set of time series variables? Providing guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests. In addition, it covers such topics as: joint stationarity; testing for cointegration; testing for causality; and model order and forecast accuracy. Related models explained include transfer function, vector autoregression and error correction models.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
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