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, ...)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. 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.
A tibble::tibble with one row for each coefficient and columns:
The term in the nonlinear model being estimated and tested
The estimated coefficient
The standard error from the linear model
If conf.int = TRUE, also returns
low end of confidence interval
high end of confidence interval
Other Arima tidiers:
glance.Arima()
# NOT RUN {
fit <- arima(lh, order = c(1, 0, 0))
tidy(fit)
glance(fit)
# }
Run the code above in your browser using DataLab