Flexible and efficient estimating equations for variogram estimation
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Type
ArticleAuthors
Sun, Ying
Chang, Xiaohui
Guan, Yongtao
KAUST Department
Applied Mathematics and Computational Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Statistics Program
Date
2018-01-11Online Publication Date
2018-01-11Print Publication Date
2018-06Permanent link to this record
http://hdl.handle.net/10754/626860
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Variogram estimation plays a vastly important role in spatial modeling. Different methods for variogram estimation can be largely classified into least squares methods and likelihood based methods. A general framework to estimate the variogram through a set of estimating equations is proposed. This approach serves as an alternative approach to likelihood based methods and includes commonly used least squares approaches as its special cases. The proposed method is highly efficient as a low dimensional representation of the weight matrix is employed. The statistical efficiency of various estimators is explored and the lag effect is examined. An application to a hydrology dataset is also presented.Citation
Sun Y, Chang X, Guan Y (2018) Flexible and efficient estimating equations for variogram estimation. Computational Statistics & Data Analysis. Available: http://dx.doi.org/10.1016/j.csda.2017.12.006.Publisher
Elsevier BVAdditional Links
http://www.sciencedirect.com/science/article/pii/S016794731830001Xae974a485f413a2113503eed53cd6c53
10.1016/j.csda.2017.12.006