Description Usage Arguments Value Examples
The Bayesian implementation of ridge regression. Plug-in pseudovariances are used for
the binomial and poisson likelihood functions.
Model Specification:
Plugin Pseudo-Variances:
1 2 3 4 |
formula |
the model formula |
data |
a data frame. |
family |
one of "gaussian", "st" (Student-t with nu = 3), "binomial", or "poisson". |
lambda.prior |
either "dmouch" (the default) or "gamma" |
log_lik |
Should the log likelihood be monitored? The default is FALSE. |
iter |
How many post-warmup samples? Defaults to 10000. |
warmup |
How many warmup samples? Defaults to 1000. |
adapt |
How many adaptation steps? Defaults to 2000. |
chains |
How many chains? Defaults to 4. |
thin |
Thinning interval. Defaults to 1. |
method |
Defaults to "rjparallel". For an alternative parallel option, choose "parallel". Otherwise, "rjags" (single core run). |
cl |
Use parallel::makeCluster(# clusters) to specify clusters for the parallel methods. Defaults to two cores. |
... |
Other arguments to run.jags. |
a runjags object
1 | ridge()
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