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 cross 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 spec
tidy(x, ...)

Arguments

x

A spec object created by stats::spectrum().

...

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.

See also

tidy(), stats::spectrum()

Other time series tidiers: tidy.acf, tidy.ts, tidy.zoo

Value

A tibble::tibble() with columns:

Examples

spc <- spectrum(lh)
tidy(spc)
#> # A tibble: 24 x 2 #> freq spec #> <dbl> <dbl> #> 1 0.0208 0.0912 #> 2 0.0417 0.331 #> 3 0.0625 0.836 #> 4 0.0833 1.17 #> 5 0.104 0.350 #> 6 0.125 1.51 #> 7 0.146 0.328 #> 8 0.167 0.618 #> 9 0.188 0.320 #> 10 0.208 0.0675 #> # ... with 14 more rows
library(ggplot2) ggplot(tidy(spc), aes(freq, spec)) + geom_line()