# Choosing between models - a business view

We discussed how we use the AIC to choose between models. The standard definition of the AIC is:

AIC = -2 * log-likelihood + 2 * number of parameters

However, this is a statistician's view of a model, where the only criterion for including a parameter is whether it is statistically significant. A business view might be different, as each extra parameter in a system will cost you money. IT systems have to be specified, programmed, tested and maintained, for example, and IT staff are not cheap. Each extra parameter might therefore cost you £5,000 in development costs (say), so you might be inclined to only include parameters if they are *really* significant. One way of doing this is to increase the penalty for the number of parameters in the definition of the AIC as follows:

AIC = -2 * log-likelihood + *N* * number of parameters

where *N* can be 2 for a statistical view, as before. However, if you felt that complexity was expensive, you can be particularly demanding of extra parameters and set *N* to 3, 4 or 5 (say). Thus, the AIC is not only a tool for the statistician, but it can also be adapted to help make business decisions.

## Previous posts

### Choosing between models

**Tags:**Filter information matrix by tag: AIC, Filter information matrix by tag: log-likelihood, Filter information matrix by tag: model fit

## Add new comment