Well-behaved Statistic

A well-behaved statistic is a term sometimes used in the theory of statistics to describe part of a procedure. This usage is broadly similar to the use of well-behaved in more general mathematics. It is essentially an assumption about the formulation of an estimation procedure (which entails the specification of an estimator or statistic) that is used to avoid giving extensive details about what conditions need to hold. In particular it means that the statistic is not an unusual one in the context being studied. Due to this, the meaning attributed to well-behaved statistic may vary from context to context.

The present article is mainly concerned with the context of data mining procedures applied to statistical inference and, in particular, to the group of computationally intensive procedure that have been called algorithmic inference.