Ordinary cokriging of the threshold indicator with the uniform (rank)
transform (Sullivan 1984), with exponential direct and cross covariances
given as c(nugget, sill, range). Identical to the Python arm
morie.fn.probkrig.
Usage
ProbabilityKriging(coords, values, targets, threshold, cov_i, cov_u, cov_iu)
Arguments
- coords
Data coordinates (two-column).
- values
Data values.
- targets
Prediction locations (two-column).
- threshold
Threshold z_k.
- cov_i, cov_u, cov_iu
Indicator, uniform and cross covariances.
Value
A list with the estimates, clipped probabilities and weights.
References
Sullivan, J. (1984). Conditional recovery estimation through
probability kriging: theory and practice. Geostatistics for Natural
Resources Characterization, Reidel, 365-384.
Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation.
Oxford University Press.
Examples
P <- rbind(c(0, 0), c(1, 0), c(0, 1), c(1, 1))
ProbabilityKriging(P, c(1, 3, 2, 4), rbind(c(0.5, 0.5)), 2.5,
c(0, 0.25, 1), c(0, 0.08, 1), c(0, 0.1, 1))$estimate
#> [1] 0.5
