Check if Prior is Informative
Performs a simple test to check whether the prior is informative to the posterior. This idea, and the accompanying heuristics, were discussed in this blogpost.
check_prior(model, method = "gelman", simulate_priors = TRUE, ...)
model |
A |
method |
Can be |
simulate_priors |
Should prior distributions be simulated using
|
... |
Currently not used. |
A data frame with two columns: The parameter names and the quality
of the prior (which might be "informative"
, "uninformative"
)
or "not determinable"
if the prior distribution could not be
determined).
https://statmodeling.stat.columbia.edu/2019/08/10/
## Not run: library(bayestestR) if (require("rstanarm")) { model <- stan_glm(mpg ~ wt + am, data = mtcars, chains = 1, refresh = 0) check_prior(model, method = "gelman") check_prior(model, method = "lakeland") # An extreme example where both methods diverge: model <- stan_glm(mpg ~ wt, data = mtcars[1:3, ], prior = normal(-3.3, 1, FALSE), prior_intercept = normal(0, 1000, FALSE), refresh = 0 ) check_prior(model, method = "gelman") check_prior(model, method = "lakeland") plot(si(model)) # can provide visual confirmation to the Lakeland method } ## End(Not run)
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