%0 Journal Article %A Hazem M. Al-Mofleh and John E. Daniels and Joseph W. McKean %D 2016 %J International Journal of Mathematical and Computational Sciences %B World Academy of Science, Engineering and Technology %I Open Science Index 110, 2016 %T Robust Variogram Fitting Using Non-Linear Rank-Based Estimators %U https://publications.waset.org/pdf/10004024 %V 110 %X In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates. %P 73 - 82