Explanatory variables in ADAM
Ivan Svetunkov · 2023
In real life, the need for explanatory variables arises when there are some external factors that have relation with the response variable and impact the final forecasts and their accuracy. This chapter discusses the main aspects of ADAM with explanatory variables, how it is formulated, and how the more advanced models can be built upon it. The model discussed in the chapter assumes particular dynamics of parameters, aligning with what the conventional ETS assumes: regression parameters are correlated with the states of the model. When dealing with categorical variables in a regression context, they are typically expanded to a set of dummy variables. Finally, the distance negatively impacts the incidents as well, reducing it on average by 0.1% for each 1% increase in the distance. Finally, adam has some shortcuts when a matrix of variables is provided with no formula, assuming that the necessary expansion has already been done.