Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
# S3 method for glmRob
tidy(x, ...)
A glmRob
object returned from robust::glmRob()
.
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in ...
, where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass conf.lvel = 0.9
, all computation will
proceed using conf.level = 0.95
. Additionally, if you pass
newdata = my_tibble
to an augment()
method that does not
accept a newdata
argument, it will use the default value for
the data
argument.
For tidiers for robust models from the MASS package see
tidy.rlm()
.
Other robust tidiers:
augment.lmRob()
,
glance.glmRob()
,
glance.lmRob()
,
tidy.lmRob()
# feel free to ignore the following line—it allows {broom} to supply
# examples without requiring the model-supplying package to be installed.
if (requireNamespace("robust", quietly = TRUE)) {
# load libraries for models and data
library(robust)
# fit model
gm <- glmRob(am ~ wt, data = mtcars, family = "binomial")
# summarize model fit with tidiers
tidy(gm)
glance(gm)
}
#> # A tibble: 1 × 5
#> deviance sigma null.deviance df.residual nobs
#> <dbl> <dbl> <dbl> <int> <int>
#> 1 19.2 0.800 44.4 30 32