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.
# S3 method for garch
glance(x, test = c("box-ljung-test", "jarque-bera-test"), ...)A garch object returned by tseries::garch().
Character specification of which hypothesis test to use. The
garch function reports 2 hypothesis tests: Jarque-Bera to residuals
and Box-Ljung to squared residuals.
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:
Test statistic used to compute the p-value
P-value
Parameter field in the htest, typically degrees of freedom
Method used to compute the statistic as a string
the data's log-likelihood under the model
the Akaike Information Criterion
the Bayesian Information Criterion
glance(), tseries::garch(), []
Other garch tidiers:
tidy.garch()