Constrained multiple indicator kriging using sequential quadratic programming

  • Authors:
  • Saeed Soltani-Mohammadi;A. Erhan Tercan

  • Affiliations:
  • Department of Mining Engineering, University of Kashan, Kashan, Iran;Department of Mining Engineering, Hacettepe University, Ankara, Turkey

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2012

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Abstract

Multiple indicator kriging (MIK) is a nonparametric method used to estimate conditional cumulative distribution functions (CCDF). Indicator estimates produced by MIK may not satisfy the order relations of a valid CCDF which is ordered and bounded between 0 and 1. In this paper a new method has been presented that guarantees the order relations of the cumulative distribution functions estimated by multiple indicator kriging. The method is based on minimizing the sum of kriging variances for each cutoff under unbiasedness and order relations constraints and solving constrained indicator kriging system by sequential quadratic programming. A computer code is written in the Matlab environment to implement the developed algorithm and the method is applied to the thickness data.