In
statistics, a
shrinkage estimator is an
estimator that, either explicitly or implicitly, incorporates the effects of
shrinkage. In loose terms this means that a naive or raw estimate is improved by combining it with other information. The term relates to the notion that the improved estimate is made closer to the value supplied by the 'other information' than the raw estimate. In this sense, shrinkage is used to
regularize ill-posed inference problems.