Data analysis tools

The following tools are implemented as modular components to be used by any data analysis technique:

• Numerous high-precision optimisation algorithms.
• Model selection (d'Auvergne and Gooley, 2003; Chen et al., 2004):
  • Akaike's Information Criteria (AIC).
  • Small sample size corrected AIC (AICc).
  • Bayesian or Schwarz Information Criteria (BIC).
  • Bootstrap model selection.
  • Single-item-out cross-validation (CV).
  • Hypothesis testing ANOVA model selection (only the model-free specific technique of Mandel et al. (1995) is supported).
• Monte Carlo simulations (error analysis for all data analysis techniques).
• Model elimination - the removal of failed models prior to model selection (d'Auvergne and Gooley, 2006).