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 orcutt
tidy(x, ...)
An orcutt
object returned from orcutt::cochrane.orcutt()
.
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.
Other orcutt tidiers:
glance.orcutt()
A tibble::tibble()
with columns:
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The standard error of the regression term.
The name of the regression term.
# feel free to ignore the following line—it allows {broom} to supply
# examples without requiring the model-supplying package to be installed.
if (requireNamespace("orcutt", quietly = TRUE)) {
# load libraries for models and data
library(orcutt)
# fit model and summarize results
reg <- lm(mpg ~ wt + qsec + disp, mtcars)
tidy(reg)
co <- cochrane.orcutt(reg)
tidy(co)
glance(co)
}
#> # A tibble: 1 × 9
#> r.squared adj.r.squared rho number.interaction dw.original p.value.original
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 0.799 0.777 0.268 7 1.50 0.0406
#> # … with 3 more variables: dw.transformed <dbl>, p.value.transformed <dbl>,
#> # nobs <int>