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 nlrq tidy(x, conf.int = FALSE, conf.level = 0.95, ...)
| x | A |
|---|---|
| conf.int | Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
| conf.level | The confidence level to use for the confidence interval
if |
| ... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble() with one row for each term in the
regression. The tibble has columns:
The name of the regression term.
The estimated value of the regression term.
The standard error of the regression term.
The value of a statistic, almost always a T-statistic, to use in a hypothesis that the regression term is non-zero.
The two-sided p-value associated with the observed statistic.
The low end of a confidence interval for the regression
term. Included only if conf.int = TRUE.
The high end of a confidence interval for the regression
term. Included only if conf.int = TRUE.
tidy(), quantreg::nlrq()
Other quantreg tidiers: augment.nlrq,
augment.rqs, augment.rq,
glance.nlrq, glance.rq,
tidy.rqs, tidy.rq