Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample fit can be a poor guide to actual forecasting effectiveness. However, post-sample model testing requires an often-consequential a priori partitioning of the data into an "in-sample"...

1. Nonlinearity in Stochastic Processes: What it Is and Why it Matters -- 2. Detecting Nonlinear Serial Dependence -- 3. How to Run the Toolkit Program on a PC -- 4. Artificially Generated Data: Size Considerations -- 5. Artificially Generated Data: Power And Model Specification Considerations...