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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 ts
tidy(x, ...)
A univariate or multivariate ts
times series object.
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 columns:
Index (i.e. date or time) for a `ts` or `zoo` object.
Name of the series (present only for multivariate time series).
The value/estimate of the component. Results from data reshaping.
series
column is only present for multivariate ts
objects.
Other time series tidiers:
tidy.acf()
,
tidy.spec()
,
tidy.zoo()
# NOT RUN {
set.seed(678)
tidy(ts(1:10, frequency = 4, start = c(1959, 2)))
z <- ts(matrix(rnorm(300), 100, 3), start = c(1961, 1), frequency = 12)
colnames(z) <- c("Aa", "Bb", "Cc")
tidy(z)
# }
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