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Refit Bayesian model as frequentist. Can be useful for comparisons.

Usage

convert_bayesian_as_frequentist(model, data = NULL, REML = TRUE)

bayesian_as_frequentist(model, data = NULL, REML = TRUE)

Arguments

model

A Bayesian model.

data

Data used by the model. If NULL, will try to extract it from the model.

REML

For mixed effects, should models be estimated using restricted maximum likelihood (REML) (TRUE, default) or maximum likelihood (FALSE)?

Examples

# \donttest{
# Rstanarm ----------------------
if (require("rstanarm")) {
  # Simple regressions
  model <- stan_glm(Sepal.Length ~ Species,
    data = iris, chains = 2, refresh = 0
  )
  bayesian_as_frequentist(model)
}
#> Loading required package: rstanarm
#> Loading required package: Rcpp
#> This is rstanarm version 2.21.3
#> - See https://mc-stan.org/rstanarm/articles/priors for changes to default priors!
#> - Default priors may change, so it's safest to specify priors, even if equivalent to the defaults.
#> - For execution on a local, multicore CPU with excess RAM we recommend calling
#>   options(mc.cores = parallel::detectCores())
#> 
#> Call:
#> stats::lm(formula = formula$conditional, data = data)
#> 
#> Coefficients:
#>       (Intercept)  Speciesversicolor   Speciesvirginica  
#>             5.006              0.930              1.582  
#> 
# }

if (FALSE) {
if (require("rstanarm")) {
  model <- stan_glm(vs ~ mpg,
    family = "binomial",
    data = mtcars, chains = 2, refresh = 0
  )
  bayesian_as_frequentist(model)

  # Mixed models
  model <- stan_glmer(Sepal.Length ~ Petal.Length + (1 | Species),
    data = iris, chains = 2, refresh = 0
  )
  bayesian_as_frequentist(model)

  model <- stan_glmer(vs ~ mpg + (1 | cyl),
    family = "binomial",
    data = mtcars, chains = 2, refresh = 0
  )
  bayesian_as_frequentist(model)
}
}