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, ...)
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
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.
library(gam)#>#>#>#> Warning: non-list contrasts argument ignoredtidy(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 NAglance(g)#> # A tibble: 1 x 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