On the rate of convergence of the Robbins–Monro's algorithm in a linear stochastic ill-posed problem with α-mixing data

Nabila Aiane and Abdelnasser Dahmani

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 13, 6694-6703

Abstract: In this paper we consider a recursive method of Robbins–Monro type to estimate the solution of the linear problem Ax = u, in which the second member is measured with α-mixing errors. We also show the almost complete convergence (a.co) of this algorithm specifying its convergence rate.

Date: 2017
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DOI: 10.1080/03610926.2015.1133825

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