Constrained interpolation and qualitative information—The soft kriging approach

Traditional interpolation algorithms, including krigings, do not account for inequality-type data less subjective qualitative information. Soft kriging formalism allows a coding of both hard data and constraint intervals as prior cumulative distribution functions (cdfs) which are interpolated into posterior cdfs. Non-Gaussian confidence intervals and various “optimal” estimates then are derived. A synthetic case study is presented.