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  "Title": "Covariance Inference and Decompositions for Tensor Datasets",
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  "Authors@R": "c(person(\"David\", \"Gerard\", email = \"gerard.1787@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0001-9450-5023\")),\nperson(\"Peter\", \"Hoff\", email = \"peter.hoff@duke.edu\", role = \"aut\"))",
  "Description": "A collection of functions for Kronecker structured\ncovariance estimation and testing under the array normal model.\nFor estimation, maximum likelihood and Bayesian equivariant\nestimation procedures are implemented. For testing, a\nlikelihood ratio testing procedure is available. This package\nalso contains additional functions for manipulating and\ndecomposing tensor data sets. This work was partially supported\nby NSF grant DMS-1505136. Details of the methods are described\nin Gerard and Hoff (2015) <doi:10.1016/j.jmva.2015.01.020> and\nGerard and Hoff (2016) <doi:10.1016/j.laa.2016.04.033>.",
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    "start_ident",
    "start_resids",
    "tr",
    "trim",
    "tsum"
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      "page": "array_bic_aic",
      "title": "Calculate the AIC and BIC.",
      "topics": [
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      ]
    },
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      "title": "Array indices.",
      "topics": [
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    },
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      "title": "Tucker product.",
      "topics": [
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      "title": "Collapse multiple modes into one mode.",
      "topics": [
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      "title": "Convert the output from 'equi_mcmc' to component covariance matrices.",
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      "title": "Demeans array data.",
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      "title": "Gibbs sampler using an invariant prior.",
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      "title": "Calculate the incredible SVD (ISVD).",
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      ]
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      "title": "Calculate the incredible higher-order LQ decomposition (HOLQ).",
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      ]
    },
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      "title": "Calculate the higher-order orthogonal iteration (HOOI).",
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      ]
    },
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      "title": "Calculate the (truncated) higher-order SVD (HOSVD).",
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      ]
    },
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      "title": "The incredible higher-order polar decomposition (IHOP).",
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      "title": "Kendall's tau measure of association.",
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      "title": "Commutation matrix.",
      "topics": [
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      "title": "Log-likelihood of array normal model.",
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      "title": "Element-wise matrix products between two lists.",
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      "title": "Calculate the likelihood ratio test statistic.",
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    },
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      "title": "Unfold a matrix.",
      "topics": [
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      "title": "Calculate a truncated multiway Takemura estimator.",
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      "title": "The left polar decomposition.",
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      "title": "Sample from the mirror-Wishart distribution.",
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