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 density
tidy(x, ...)

Arguments

x

A density object returned from stats::density().

...

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.

Value

A tibble::tibble with two columns: points x where the density is estimated, and estimated density y. When the input to the stats::density() function is an nXm matrix, as opposed to a 1Xm vector, the input matrix is first flattened into a 1X(m*n) vector and then the density function is applied as usual.

See also

tidy(), stats::density()

Other stats tidiers: tidy.dist(), tidy.ftable()