Geostatistical studies often consider many variables; geotechnical and metallurgical properties, porosity, permeability and size distributions. Multivariate transformations, such as principal component analysis, the stepwise conditional transform or projection pursuit multivariate transform may be applied for decorrelation or transformation to a multivariate Gaussian distribution. Multivariate probability distributions may be fit with kernel density estimates or Gaussian mixture models. Complex relationships may be understood with nonlinear regression techniques such as alternating conditional expectations.
- Multidimensional Scaling (see source code on GitHub)
- Projection Pursuit Multivariate Transform
- Principal Component Analysis
- Aggregating Variables into a Super Secondary Variable