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 class 'mnr'
augment(x, data = x$data, ...)an mnr object created by
maximum_normed_residual()
a data.frame or
tibble::tibble()
containing the original data that was passed to
maximum_normed_residual
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