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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | sim2Dpredictr_0.1.1.tar.gz |
194.1 KiB |
0.1.1 |
rolling linux/noble R-4.5 | sim2Dpredictr_0.1.1.tar.gz |
194.0 KiB |
0.1.1 |
rolling source/ R- | sim2Dpredictr_0.1.1.tar.gz |
117.4 KiB |
0.1.1 |
latest linux/jammy R-4.5 | sim2Dpredictr_0.1.1.tar.gz |
194.1 KiB |
0.1.1 |
latest linux/noble R-4.5 | sim2Dpredictr_0.1.1.tar.gz |
194.0 KiB |
0.1.1 |
latest source/ R- | sim2Dpredictr_0.1.1.tar.gz |
117.4 KiB |
0.1.1 |
2026-04-26 source/ R- | sim2Dpredictr_0.1.1.tar.gz |
117.4 KiB |
0.1.1 |
2026-04-23 source/ R- | sim2Dpredictr_0.1.1.tar.gz |
117.4 KiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | sim2Dpredictr_0.1.1.zip |
196.3 KiB |
0.1.1 |
2025-04-20 source/ R- | sim2Dpredictr_0.1.1.tar.gz |
117.4 KiB |