Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
Character specification of which hypothesis test to use. The
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
tibble::tibble() with exactly one row and columns:
Akaike's Information Criterion for the model.
Bayesian Information Criterion for the model.
The log-likelihood of the model. [stats::logLik()] may be a useful reference.
Which method was used.
Number of observations used.
P-value corresponding to the test statistic.
Parameter field in the htest, typically degrees of freedom.