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 Gam tidy(x, ...)
x | A |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Tidy gam
objects created by calls to mgcv::gam()
with
tidy.gam()
.
tidy()
, gam::gam()
, tidy.anova()
, tidy.gam()
Other gam tidiers:
glance.Gam()
A tibble::tibble()
with columns:
Degrees of freedom used by this term in the model.
Mean sum of squares. Equal to total sum of squares divided by degrees of freedom.
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.
Sum of squares explained by this term.
The name of the regression term.
if (requireNamespace("gam", quietly = TRUE)) { library(gam) g <- gam(mpg ~ s(hp, 4) + am + qsec, data = mtcars) tidy(g) glance(g) } #> Loading required package: splines #> Loading required package: foreach #> Loaded gam 1.20 #> # A tibble: 1 × 7 #> df logLik AIC BIC deviance df.residual nobs #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> #> 1 7.00 -76.0 162. 169. 180. 25.0 32