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, ...)
x | A univariate or multivariate |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
series
column is only present for multivariate ts
objects.
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.
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 #> # … with 290 more rows