Augment accepts an mnr object (returned from the function
maximum_normed_residual()) and a dataset and adds the column
.outlier to the dataset. The column .outlier is a logical
vector indicating whether each observation is an outlier.
When passing data into augment using the data argument,
the data must be exactly the data that was passed to
maximum_normed_residual.
# S3 method for mnr augment(x, data = x$data, ...)
| x | an |
|---|---|
| data | a |
| ... | Additional arguments. Not used. Included only to match generic signature. |
When data is supplied, augment returns data, but with
one column appended. When data is not supplied, augment
returns a new tibble::tibble() with the column
values containing the original values used by
maximum_normed_residaul plus one additional column. The additional
column is:
.outler a logical value indicating whether the observation
is an outlier
data <- data.frame(strength = c(80, 98, 96, 97, 98, 120)) m <- maximum_normed_residual(data, strength) # augment can be called with the original data augment(m, data)#> strength .outlier #> 1 80 FALSE #> 2 98 FALSE #> 3 96 FALSE #> 4 97 FALSE #> 5 98 FALSE #> 6 120 FALSE## strength .outlier ## 1 80 FALSE ## 2 98 FALSE ## 3 96 FALSE ## 4 97 FALSE ## 5 98 FALSE ## 6 120 FALSE # or augment can be called without the orignal data and it will be # reconstructed augment(m)#> # A tibble: 6 × 2 #> values .outlier #> <dbl> <lgl> #> 1 80 FALSE #> 2 98 FALSE #> 3 96 FALSE #> 4 97 FALSE #> 5 98 FALSE #> 6 120 FALSE## # A tibble: 6 x 2 ## values .outlier ## <dbl> <lgl> ## 1 80 FALSE ## 2 98 FALSE ## 3 96 FALSE ## 4 97 FALSE ## 5 98 FALSE ## 6 120 FALSE