Glance accepts a model object and returns a tibble::tibble()
with exactly one row of model summaries. The summaries are typically
goodness of fit measures, p-values for hypothesis tests on residuals,
or model convergence information.
Glance never returns information from the original call to the modelling function. This includes the name of the modelling function or any arguments passed to the modelling function.
Glance does not calculate summary measures. Rather, it farms out these
computations to appropriate methods and gathers the results together.
Sometimes a goodness of fit measure will be undefined. In these cases
the measure will be reported as NA.
# S3 method for rq
glance(x, ...)An rq object returned from quantreg::rq().
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in ..., where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass conf.lvel = 0.9, all computation will
proceed using conf.level = 0.95. Additionally, if you pass
newdata = my_tibble to an augment() method that does not
accept a newdata argument, it will use the default value for
the data argument.
A one-row tibble::tibble with columns:
quantile estimated
the data's log-likelihood under the model
the Akaike Information Criterion
the Bayesian Information Criterion
residual degrees of freedom
Only models with a single tau value may be passed.
For multiple values, please use a purrr::map() workflow instead, e.g.
taus %>% map(function(tau_val) rq(y ~ x, tau = tau_val)) %>% map_dfr(glance)
Other quantreg tidiers:
augment.nlrq(),
augment.rqs(),
augment.rq(),
glance.nlrq(),
tidy.nlrq(),
tidy.rqs(),
tidy.rq()