jmleach-bst/sim2Dpredictr: Simulate Outcomes Using Spatially Dependent Design Matrices
Provides tools for simulating spatially dependent predictors (continuous or binary), which are used to generate scalar outcomes in a (generalized) linear model framework. Continuous predictors are generated using traditional multivariate normal distributions or Gauss Markov random fields with several correlation function approaches (e.g., see Rue (2001) <doi:10.1111/1467-9868.00288> and Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>), while binary predictors are generated using a Boolean model (see Cressie and Wikle (2011, ISBN: 978-0-471-69274-4)). Parameter vectors exhibiting spatial clustering can also be easily specified by the user.
Getting started
Browse package contents
Package details |
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| Maintainer | |
| License | GPL-3 |
| Version | 0.1.1 |
| URL | https://github.com/jmleach-bst/sim2Dpredictr |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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