Tidy a(n) gam object
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 class 'gam' tidy( x, parametric = FALSE, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ... )
x |
A |
parametric |
Logical indicating if parametric or smooth terms should
be tidied. Defaults to |
conf.int |
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level |
The confidence level to use for the confidence interval
if |
exponentiate |
Logical indicating whether or not to exponentiate the
the coefficient estimates. This is typical for logistic and multinomial
regressions, but a bad idea if there is no log or logit link. Defaults
to |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
When parametric = FALSE
return columns edf
and ref.df
rather
than estimate
and std.error
.
A tibble::tibble()
with columns:
estimate |
The estimated value of the regression term. |
p.value |
The two-sided p-value associated with the observed statistic. |
statistic |
The value of a T-statistic to use in a hypothesis that the regression term is non-zero. |
std.error |
The standard error of the regression term. |
term |
The name of the regression term. |
edf |
The effective degrees of freedom. Only reported when 'parametric = FALSE' |
ref.df |
The reference degrees of freedom. Only reported when 'parametric = FALSE' |
Other mgcv tidiers:
glance.gam()
if (requireNamespace("mgcv", quietly = TRUE)) { g <- mgcv::gam(mpg ~ s(hp) + am + qsec, data = mtcars) tidy(g) tidy(g, parametric = TRUE) glance(g) augment(g) }
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