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Tidying methods for decomposed time series

Source: R/tidiers_decomposed_ts.R
tidiers_decomposed_ts.Rd

Tidying methods for decomposed time series

Usage

# S3 method for decomposed.ts
sw_tidy_decomp(x, timetk_idx = FALSE, rename_index = "index", ...)

Arguments

x

An object of class "decomposed.ts"

timetk_idx

Used with sw_augment and sw_tidy_decomp. When TRUE, uses a timetk index (irregular, typically date or datetime) if present.

rename_index

Used with sw_augment and sw_tidy_decomp. A string representing the name of the index generated.

...

Not used.

Value

sw_tidy_decomp() returns a tibble with the following time series attributes:

  • index: An index is either attempted to be extracted from the model or a sequential index is created for plotting purposes

  • season: The seasonal component

  • trend: The trend component

  • random: The error component

  • seasadj: observed - season

See also

decompose()

Examples

library(dplyr)
library(forecast)

fit_decomposed <- USAccDeaths %>%
    decompose()

sw_tidy_decomp(fit_decomposed)
#> # A tibble: 72 × 6
#>    index     observed season trend random seasadj
#>    <yearmon>    <dbl>  <dbl> <dbl>  <dbl>   <dbl>
#>  1 Jan 1973      9007  -806.   NA    NA     9813.
#>  2 Feb 1973      8106 -1523.   NA    NA     9629.
#>  3 Mar 1973      8928  -741.   NA    NA     9669.
#>  4 Apr 1973      9137  -515.   NA    NA     9652.
#>  5 May 1973     10017   340.   NA    NA     9677.
#>  6 Jun 1973     10826   745.   NA    NA    10081.
#>  7 Jul 1973     11317  1679. 9599.   38.2   9638.
#>  8 Aug 1973     10744   986. 9500.  258.    9758.
#>  9 Sep 1973      9713  -109. 9416.  406.    9822.
#> 10 Oct 1973      9938   264. 9349.  325.    9674.
#> # ℹ 62 more rows