@article{(Open Science Index):https://publications.waset.org/pdf/10004024,
	  title     = {Robust Variogram Fitting Using Non-Linear Rank-Based Estimators},
	  author    = {Hazem M. Al-Mofleh and  John E. Daniels and  Joseph W. McKean},
	  country	= {},
	  institution	= {},
	  abstract     = {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.
},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {10},
	  number    = {2},
	  year      = {2016},
	  pages     = {73 - 82},
	  ee        = {https://publications.waset.org/pdf/10004024},
	  url   	= {https://publications.waset.org/vol/110},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 110, 2016},
	}