loess_tidiers: Augmenting methods for loess models
Description
This method augments the original data with information
on the fitted values and residuals, and optionally the
standard errors.
Usage
"augment"(x, data = stats::model.frame(x), newdata, ...)
Arguments
x
A "loess" object
data
Original data, defaults to the extracting it from the model
newdata
If provided, performs predictions on the new data
...
extra arguments
Value
When newdata is not supplied augment.loess
returns one row for each observation with three columns added
to the original data:
.fitted
Fitted values of model
.se.fit
Standard errors of the fitted values
.resid
Residuals of the fitted values
When newdata is supplied augment.loess returns
one row for each observation with one additional column:
.fitted
Fitted values of model
.se.fit
Standard errors of the fitted values
Details
When the modeling was performed with na.action = "na.omit"
(as is the typical default), rows with NA in the initial data are omitted
entirely from the augmented data frame. When the modeling was performed
with na.action = "na.exclude", one should provide the original data
as a second argument, at which point the augmented data will contain those
rows (typically with NAs in place of the new columns). If the original data
is not provided to augment and na.action = "na.exclude", a
warning is raised and the incomplete rows are dropped.
lo <- loess(mpg ~ wt, mtcars)
augment(lo)
# with all columns of original dataaugment(lo, mtcars)
# with a new datasetaugment(lo, newdata = head(mtcars))