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  "Title": "Automatic Fixed Rank Kriging",
  "Description": "Automatic fixed rank kriging for (irregularly located)\nspatial data using a class of basis functions with\nmulti-resolution features and ordered in terms of their\nresolutions. The model parameters are estimated by maximum\nlikelihood (ML) and the number of basis functions is determined\nby Akaike's information criterion (AIC). For spatial data with\neither one realization or independent replicates, the ML\nestimates and AIC are efficiently computed using their\nclosed-form expressions when no missing value occurs. Details\nregarding the basis function construction, parameter\nestimation, and AIC calculation can be found in Tzeng and Huang\n(2018) <doi:10.1080/00401706.2017.1345701>. For data with\nmissing values, the ML estimates are obtained using the\nexpectation- maximization algorithm. Apart from the number of\nbasis functions, there are no other tuning parameters, making\nthe method fully automatic. Users can also include a stationary\nstructure in the spatial covariance, which utilizes\n'LatticeKrig' package.",
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  "Date": "2026-01-15",
  "Author": "ShengLi Tzeng [aut, cre], Hsin-Cheng Huang [aut], Wen-Ting Wang\n[ctb], Douglas Nychka [ctb]",
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    "toSpMat",
    "uniquecombs",
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