Tidy a(n) rqs object
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 class 'rqs' tidy(x, se.type = "rank", conf.int = FALSE, conf.level = 0.95, ...)
x |
An |
se.type |
Character specifying the method to use to calculate
standard errors. Passed to |
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 passed to |
If se.type = "rank" confidence intervals are calculated by
summary.rq. When only a single predictor is included in the model,
no confidence intervals are calculated and the confidence limits are
set to NA.
A tibble::tibble() with columns:
conf.high |
Upper bound on the confidence interval for the estimate. |
conf.low |
Lower bound on the confidence interval for the estimate. |
estimate |
The estimated value of the regression term. |
p.value |
The two-sided p-value associated with the observed statistic. |
statistic |
The value of a T-statistic to use in a hypothesis that the regression term is non-zero. |
std.error |
The standard error of the regression term. |
term |
The name of the regression term. |
quantile |
Linear conditional quantile. |
Other quantreg tidiers:
augment.nlrq(),
augment.rqs(),
augment.rq(),
glance.nlrq(),
glance.rq(),
tidy.nlrq(),
tidy.rq()
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