Robust Variogram Fitting Using Non-Linear Rank-Based Estimators
| Main Authors: | Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2016
|
| Subjects: | |
| Online Access: |
https://zenodo.org/record/1112318 |
Daftar Isi:
- 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.