r descr_models("logistic_reg", "stan")

Tuning Parameters

This engine has no tuning parameters.

Important engine-specific options

Some relevant arguments that can be passed to set_engine():

See [rstan::sampling()] and [rstanarm::priors()] for more information on these and other options.

Translation from parsnip to the original package

logistic_reg() %>% 
  set_engine("stan") %>% 
  translate()

Note that the refresh default prevents logging of the estimation process. Change this value in set_engine() to show the MCMC logs.

Preprocessing requirements


Other details

For prediction, the "stan" engine can compute posterior intervals analogous to confidence and prediction intervals. In these instances, the units are the original outcome and when std_error = TRUE, the standard deviation of the posterior distribution (or posterior predictive distribution as appropriate) is returned.

Case weights


Examples

The "Fitting and Predicting with parsnip" article contains examples for logistic_reg() with the "stan" engine.

References



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parsnip documentation built on Aug. 18, 2023, 1:07 a.m.