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  "Title": "Simulate Outcomes Using Spatially Dependent Design Matrices",
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  "Description": "Provides tools for simulating spatially dependent\npredictors (continuous or binary), which are used to generate\nscalar outcomes in a (generalized) linear model framework.\nContinuous predictors are generated using traditional\nmultivariate normal distributions or Gauss Markov random fields\nwith several correlation function approaches (e.g., see Rue\n(2001) <doi:10.1111/1467-9868.00288> and Furrer and Sain (2010)\n<doi:10.18637/jss.v036.i10>), while binary predictors are\ngenerated using a Boolean model (see Cressie and Wikle (2011,\nISBN: 978-0-471-69274-4)). Parameter vectors exhibiting spatial\nclustering can also be easily specified by the user.",
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  "Repository": "https://jmleach-bst.r-universe.dev",
  "Date/Publication": "2024-02-29 18:39:07 UTC",
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