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 cross 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, ...)

Arguments

x

A Gam object returned from a call to gam::gam().

...

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.

Details

Tidy gam objects created by calls to mgcv::gam() with tidy.gam().

See also

Value

A tibble::tibble() with columns:

df

Degrees of freedom used by this term in the model.

meansq

Mean sum of squares. Equal to total sum of squares divided by degrees of freedom.

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.

sumsq

Sum of squares explained by this term

term

The name of the regression term.

Examples

library(gam)
#> Loading required package: splines
#> Loaded gam 1.15
g <- gam(mpg ~ s(hp, 4) + am + qsec, data = mtcars) tidy(g)
#> # A tibble: 4 x 6 #> term df sumsq meansq statistic p.value #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 s(hp, 4) 1 678. 678. 94.4 5.73e-10 #> 2 am 1 113. 113. 15.7 5.52e- 4 #> 3 qsec 1 0.0263 0.0263 0.00366 9.52e- 1 #> 4 Residuals 25.0 180. 7.19 NA NA
#> # A tibble: 1 x 6 #> df logLik AIC BIC deviance df.residual #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 7.00 -76.0 162. 169. 180. 25.0