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 class '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 passconf.lvel = 0.9
, all computation will proceed usingconf.level = 0.95
. Two exceptions here are:
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