Truncated Stochastic Approximation with Moving Bounds: Convergence

Teo Sharia

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arXiv · 1101.0031

Truncated Stochastic Approximation with Moving Bounds: Convergence

Teo Sharia

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Abstract

In this paper we propose a wide class of truncated stochastic approximation procedures with moving random bounds. While we believe that the proposed class of procedures will find its way to a wider range of applications, the main motivation is to accommodate applications to parametric statistical estimation theory. Our class of stochastic approximation procedures has three main characteristics: truncations with random moving bounds, a matrix valued random step-size sequence, and dynamically changing random regression function. We establish convergence and consider several examples to illustrate the results.

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Teo Sharia. 2012-05-02. Truncated Stochastic Approximation with Moving Bounds: Convergence. https://arxiv.org/abs/1101.0031

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