@article{gledocs_11858_7102,
author = {Tolosana-Delgado, Raimon and Pawlowsky-Glahn, Vera and Egozcue, Juan-Jose},
title = {Indicator Kriging without Order Relation Violations},
year = {2008},
volume = {40},
number = {3},
pages = {327-347},
publisher = {Springer-Verlag},
publisher = {Springer-Verlag},
abstract = {Indicator kriging (IK) is a spatial interpolation technique aimed at estimating the conditional cumulative distribution function (ccdf) of a variable at an unsampled location. Obtained results form a discrete approximation to this ccdf, and its corresponding discrete probability density function (cpdf) should be a vector, where each component gives the probability of an occurrence of a class. Therefore, this vector must have positive components summing up to one, like in a composition in the simplex. This suggests a simplicial approach to IK, based on the algebraic-geometric structure of this sample space: simplicial IK actually works with log-odds. Interpolated log-odds can afterwards be easily re-expressed as the desired cpdf or ccdf. An alternative but equivalent approach may also be based on log-likelihoods. Both versions of the method avoid by construction all conventional IK standard drawbacks: estimates are always within the (0,1) interval and present no order-relation problems (either with kriging or co-kriging). Even the modeling of indicator structural functions is clarified.},
note = { \url {http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/7102}},
note = { \url {http://dx.doi.org/10.23689/fidgeo-2789}},
}