In statistics and decision theory a loss function is a function that maps an event (probability theory)|event onto a real number intuitively representing some cost associated with the event. Typically it is used for parameter estimation, and the event in question is some function of the difference between estimated and true values for an instance of data. In the context of economics, for example, this is usually economic cost or Regret (decision theory)|regret. In Statistical classification|classification, it is the penalty for an incorrect classification of an example. In actuarial science, it is used in an insurance context to model benefits paid over premiums.