R: Augmenting methods for loess models

loess_tidiers {broom} | R Documentation

## 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

    ## S3 method for class 'loess'
    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

### 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.

### 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

### See Also

na.action

### Examples

    lo <- loess(mpg ~ wt, mtcars)
    augment(lo)

    # with all columns of original data
    augment(lo, mtcars)

    # with a new dataset
    augment(lo, newdata = head(mtcars))

[Package broom version 0.4.4 Index]