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 Arima
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

## Arguments

x |
An object of class `Arima` created by `stats::arima()` . |

conf.int |
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to `FALSE` . |

conf.level |
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` . 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. |

## See also

## Value

A `tibble::tibble()`

with columns:

conf.highUpper bound on the confidence interval for the estimate.

conf.lowLower bound on the confidence interval for the estimate.

estimateThe estimated value of the regression term.

std.errorThe standard error of the regression term.

termThe name of the regression term.

## Examples

#> # A tibble: 2 x 3
#> term estimate std.error
#> <fct> <dbl> <dbl>
#> 1 ar1 0.574 0.116
#> 2 intercept 2.41 0.147

#> # A tibble: 1 x 5
#> sigma logLik AIC BIC nobs
#> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 0.444 -29.4 64.8 70.4 48