Lists the parameter names and aliases that
hypothesis_BF() accepts for a fitted model, with the tests that it runs
on each of them.
hypothesis_quantities(object, ...)
# Default S3 method
hypothesis_quantities(object, transform_scaled = NULL, ...)
# S3 method for class 'BayesTools_fit'
hypothesis_quantities(object, transform_scaled = NULL, ...)a fitted model with a hypothesis_provider() method, for
example a BayesTools_fit.
unused; unused arguments warn.
whether the rendered statements test coefficients of
scaled predictors on the original scale (TRUE) or the fitted scale
(FALSE). The default NULL is the default of the provider
(FALSE for a BayesTools_fit).
A data frame with the columns alias (a name that
hypothesis_BF() resolves to the row's quantity when the row's
component is passed as the argument that selects the component of the
model, which the provider names in its component_argument: the
namespace argument for a BayesTools_fit; a name shared by
several quantities of a component is not listed), parameter,
component, term, bracket (a
parameter[level] template for fitted factor terms, or a concrete
level selector for each marginal-mean row), point_test,
direction_test, contrast_test (NA for quantities
without levels), point_test_methods, contrast_test_methods,
and reason (the refusals of the rendered statements).
The eligibility columns render the plans that
hypothesis_BF_model() executes (see its details) for the statements
<q> = <null> (point tests), <q> > <null> (directional and
interval tests), and, for factor terms, <level> = <other level>
(level contrasts) of every quantity q. The null value is 0; when 0
is a prior point mass, a support boundary without a regular prior
ordinate, or outside the support (for example, a gated random-effect
standard deviation or a variance proportion), the point test is rendered
at an interior value of the support instead (the midpoint of a bounded
support, one unit inside a half-bounded support, and 1 otherwise): point
hypotheses at such values follow the per-value rules of
hypothesis_BF_model(). A factor term lists the point-test methods
available for all of its levels that the contrast does not fix, and the
contrast-test methods available for all pairs of its levels. Region tests
do not use a density method. The methods are the registered density
backends that are advertised (hypothesis_density_backends(); the normal
approximation is a rough check and is not listed).