Running a model
The smooth trend line you saw in the plots of yield over time use a generalized additive model (GAM) to determine where the line should lie. This sort of model is ideal for fitting nonlinear curves. So we can make predictions about future yields, let's explicitly run the model. The syntax for running this GAM takes the following form.
gam(response ~ s(explanatory_var1) + explanatory_var2, data = dataset)
Here, s()
means "make the variable smooth", where smooth very roughly means nonlinear.
mgcv
and dplyr
are loaded; the corn
and wheat
datasets are available and have been expanded to include metric units and census region information.
This exercise is part of the course
Introduction to Writing Functions in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Run a generalized additive model of yield vs. smoothed year and census region
___(___ ~ s(___) + ___, data = ___)