Recursive estimators for stationary, strong mixing processes--a representation theorem and asymptotic distributions

Jan-Eric Englund, Ulla Holst and David Ruppert

Stochastic Processes and their Applications, 1989, vol. 31, issue 2, 203-222

Abstract: Many generalizations of the Robbins-Monro process have been proposed for the purpose of recursive estimation. In this paper it is shown that the recursive estimates can be represented as sums of possibly dependent random variables and can therefore be studied using limit theorems for sums. One application which is particularly studied is recursive M-estimators of location and scale for dependent strong mixing sequences.

Date: 1989
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