Theory

The theoretical documentation. This contains an in-depth description of all algorithms.

• Data analysis
  • Comparison of two samples
  • Estimation of a parametric model
  • Calibration
  • Analysis of the goodness of fit of a parametric model
  • Detection and quantification of dependencies
  • Regression
  • Estimating a quantile
• Probabilistic modeling
  • Parametric models
  • Copulas
  • Affine combination of independent univariate random variables
  • Stochastic process
• Meta modeling
  • General purpose surrogate models
  • Functional chaos
• Reliability, sensitivity
  • Central dispersion
  • Sensitivity analysis
  • Probability of crossing a threshold
• Numerical methods
  • Uniform Random Generator
  • Distribution realizations
  • Sphere sampling method
  • Optimization Algorithms
  • Least squares problems numerical methods
  • Isoprobabilistic transformation