In statistics, an additive model (AM) is a nonparametric regression method.

There are two basic processes used by the model maker to create models: additive and subtractive.

In statistics, the backfitting algorithm is a simple iterative procedure used to fit a generalized additive model.

An additive model that integrated both models.

Linear, additive models are easier to work with than more complex mathematical models.

Differences in ds only measure the amount of interaction in an additive model.

For example, they critique the additive model, in which the whole will never be greater (or lesser) than the sum of it parts.

Thus, for a response Y and two variables x and x an additive model would be:

Note an attribute of the total intensity in the additive model.

These are obscured by what I have called the additive model of cultural diversity.