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    Flexible and efficient estimating equations for variogram estimation

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    Type
    Article
    Authors
    Sun, Ying cc
    Chang, Xiaohui
    Guan, Yongtao
    KAUST Department
    Applied Mathematics and Computational Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Statistics Program
    Date
    2018-01-11
    Online Publication Date
    2018-01-11
    Print Publication Date
    2018-06
    Permanent link to this record
    http://hdl.handle.net/10754/626860
    
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    Abstract
    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 BV
    Journal
    Computational Statistics & Data Analysis
    DOI
    10.1016/j.csda.2017.12.006
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S016794731830001X
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.csda.2017.12.006
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; Statistics Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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