Model-based methods quantify changes in ‘memory’ and variance properties of a time series by attempting to fit a model to the time series.

Model-based methods currently include:

• Nonparametric drift-diffusion-jump models
• Time-varying AR(p) models
• Threshold AR(p) models
• Potential analysis
• Generalized models