Tidy a(n) lmRob object

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 lmRob
tidy(x, ...)

Arguments

x

A lmRob object returned from robust::lmRob().

...

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.

Details

For tidiers for robust models from the MASS package see tidy.rlm().

See also

robust::lmRob()

Other robust tidiers: augment.lmRob(), glance.glmRob(), glance.lmRob(), tidy.glmRob()

Examples

if (requireNamespace("robust", quietly = TRUE)) {
  library(robust)
  m <- lmRob(mpg ~ wt, data = mtcars)

  tidy(m)
  augment(m)
  glance(m)
}
#> # A tibble: 1 × 5
#>   r.squared deviance sigma df.residual  nobs
#>       <dbl>    <dbl> <dbl>       <int> <int>
#> 1     0.567     136.  2.95          30    32