R: Tidiers for lmRob and glmRob objects

robust_tidiers {broom} | R Documentation

## Tidiers for lmRob and glmRob objects

### Description

Tidying robust regression objects from the robust package. The tidy and augment methods simply pass it on to the linear model tidiers.

### Usage

    ## S3 method for class 'lmRob'
    tidy(x, ...)

    ## S3 method for class 'lmRob'
    augment(x, ...)

    ## S3 method for class 'lmRob'
    glance(x, ...)

    ## S3 method for class 'glmRob'
    tidy(x, ...)

    ## S3 method for class 'glmRob'
    augment(x, ...)

    ## S3 method for class 'glmRob'
    glance(x, ...)

### Arguments

`x` | An lmRob or glmRob object with a robust regression
`...` | Extra arguments, not used

### Value

All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.

`tidy` and `augment` return the same results as `lm_tidiers`.

On an `lmRob` `glance` returns a one-row data frame with the following columns:

`r.squared` | R-squared
`deviance` | Robust deviance
`sigma` | Residual scale estimate
`df.residual` | Number of residual degrees of freedom

On an `lmRob` `glance` returns a one-row data frame with the following columns:

`deviance` | Robust deviance
`null.deviance` | Deviance under the null model
`df.residual` | Number of residual degrees of freedom

### See Also

`lm_tidiers`, `lmRob`, `glmRob`

### Examples

    if (require("robust", quietly = TRUE)) {
      m <- lmRob(mpg ~ wt, data = mtcars)

      tidy(m)
      augment(m)
      glance(m)

      gm <- glmRob(am ~ wt, data = mtcars, family = "binomial")
      glance(gm)
    }

[Package broom version 0.4.2 Index]