jmleach-bst/ssnet: Fit Spike-and-Slab Elastic Net GLM With Spatial Priors on Parameters
This package fits generalized linear models in situations where spatial data are used as predictors of scalar outcomes. Spike-and-Slab LASSO priors are used for model selection and intrinsic conditional autoregressive regressions are used to account for spatial information in the prior probabilities for inclusion in the model.
Getting started
Browse package contents
Package details |
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| Maintainer | |
| License | GPL-3 |
| Version | 0.2.0 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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