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 across 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 rq
tidy(x, se.type = NULL, conf.int = FALSE, conf.level = 0.95, ...)An rq object returned from quantreg::rq().
Character specifying the method to use to calculate
standard errors. Passed to quantreg::summary.rq() se argument.
Defaults to "rank" if the sample size is less than 1000,
otherwise defaults to "nid".
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to FALSE.
The confidence level to use for the confidence interval
if conf.int = TRUE. Must be strictly greater than 0 and less than 1.
Defaults to 0.95, which corresponds to a 95 percent confidence interval.
Additional arguments passed to quantreg::summary.rq().
A tibble::tibble() with columns:
Upper bound on the confidence interval for the estimate.
Lower bound on the confidence interval for the estimate.
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The standard error of the regression term.
The name of the regression term.
If se.type = "rank" confidence intervals are calculated by
summary.rq and statistic and p.value values are not returned.
When only a single predictor is included in the model,
no confidence intervals are calculated and the confidence limits are
set to NA.
Other quantreg tidiers:
augment.nlrq(),
augment.rqs(),
augment.rq(),
glance.nlrq(),
glance.rq(),
tidy.nlrq(),
tidy.rqs()