%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.

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