In 1998 Genton proposed a variogram estimator claimed to be robust against outliers and compared it to Matheron's and Cressie-Hawkins' variogram estimators. Lark (2000) extended the comparison evaluating the effects of nonnormality. However, the comparison was limited to the spherical variogram model. In this paper 4 variogram estimators are compared including Genton's by using Monte Carlo simulation. Data with and without outliers were simulated using the spherical, exponential and wave models. The results showed that Genton's and the Median estimators were the best choices for contaminated data, while those of Matheron and Haslett presented better results for non-contaminated date; this latter being appropriate only for time series analysis.
Spatial statistics; robust and non-robust variogram estimators; outliers
