Now predict_gam() uses the lpmatrix
predictions which means that when excluding terms the user will have to
set a value for the excluded variable.
This is especially relevant when excluding (random) factor
smooths: the user should pick a value for the random variable in the
smooth to avoid the same predictions being output for all levels in the
random variable (see the Get started vignette for
examples).
Note that older code will still work but will produce duplicated predictions.
predict_gam() uses the lpmatrix
predictions. It is now possible to exclude any terms, smooth or
parametric.get_difference() returns difference between two
smooths.
plot.tidygam.diff method to plot difference
smooth.
Data gest and struct.
separate and sep_by arguments in
predict_gam() allow the user to separate variables in the
model that were created with interaction().
Vignette get-started.Rmd.
Error when predicting bivariate smooths (s/te/ti(),
fs/re basis functions) where only the first variable was
returned internally.
Error when plotting difference smooth with no significant difference (closes #5).
Error where get_difference() did not work when
excluding random smooths (closes #8).
First minor release of the package.
Added a NEWS.md file to track changes to the
package.