This augment method wraps augment.lm().
# S3 method for rlm
augment(x, ...)An rlm object returned by MASS::rlm().
Arguments passed on to augment.lm
dataA data.frame() or tibble::tibble() containing the original
data that was used to produce the object x. Defaults to
stats::model.frame(x) so that augment(my_fit) returns the augmented
original data. Do not pass new data to the data argument.
Augment will report information such as influence and cooks distance for
data passed to the data argument. These measures are only defined for
the original training data.
newdataA data.frame() or tibble::tibble() containing all
the original predictors used to create x. Defaults to NULL, indicating
that nothing has been passed to newdata. If newdata is specified,
the data argument will be ignored.
type.predictType of predictions to use when x is a glm object.
Passed to stats::predict.glm().
type.residualsType of residuals to use when x is a glm object.
Passed to stats::residuals.glm().
When newdata is not supplied augment.lm returns
one row for each observation, with seven columns added to the original
data:
Diagonal of the hat matrix
Estimate of residual standard deviation when corresponding observation is dropped from model
Cooks distance, cooks.distance()
Fitted values of model
Standard errors of fitted values
Residuals
Standardised residuals
Some unusual lm objects, such as rlm from MASS, may omit .cooksd and .std.resid. gam from mgcv omits .sigma.
When newdata is supplied, returns one row for each observation, with three columns added to the new data:
Fitted values of model
Standard errors of fitted values
Residuals of fitted values on the new data
Other rlm tidiers:
glance.rlm(),
tidy.rlm()