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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.

Usage

# S3 method for ts
tidy(x, ...)

Arguments

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. 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.

Details

series column is only present for multivariate ts objects.

See also

tidy(), stats::ts()

Other time series tidiers: tidy.acf(), tidy.spec(), tidy.zoo()

Value

A tibble::tibble() with columns:

index

Index (i.e. date or time) for a `ts` or `zoo` object.

series

Name of the series (present only for multivariate time series).

value

The value/estimate of the component. Results from data reshaping.

Examples


set.seed(678)

tidy(ts(1:10, frequency = 4, start = c(1959, 2)))
#> # A tibble: 10 × 2
#>    index value
#>    <dbl> <int>
#>  1 1959.     1
#>  2 1960.     2
#>  3 1960.     3
#>  4 1960      4
#>  5 1960.     5
#>  6 1960.     6
#>  7 1961.     7
#>  8 1961      8
#>  9 1961.     9
#> 10 1962.    10

z <- ts(matrix(rnorm(300), 100, 3), start = c(1961, 1), frequency = 12)
colnames(z) <- c("Aa", "Bb", "Cc")

tidy(z)
#> # A tibble: 300 × 3
#>    index series  value
#>    <dbl> <chr>   <dbl>
#>  1 1961  Aa     -0.773
#>  2 1961  Bb      0.855
#>  3 1961  Cc     -1.43 
#>  4 1961. Aa      0.933
#>  5 1961. Bb     -0.738
#>  6 1961. Cc     -2.55 
#>  7 1961. Aa      0.466
#>  8 1961. Bb      2.37 
#>  9 1961. Cc      1.22 
#> 10 1961. Aa     -1.08 
#> # ℹ 290 more rows