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 Arima
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)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 standard error of the regression term.
The name of the regression term.
An object of class Arima created by stats::arima().
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. 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. Two exceptions here are:
tidy() methods will warn when supplied an exponentiate argument if
it will be ignored.
augment() methods will warn when supplied a newdata argument if it
will be ignored.
Other Arima tidiers:
glance.Arima()
# fit model
fit <- arima(lh, order = c(1, 0, 0))
# summarize model fit with tidiers
tidy(fit)
glance(fit)
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