Consistency Results for Stationary Autoregressive Processes With Constrained Coefficients

被引：1
|
作者：
Sancetta, Alessio [1 ]
机构：
[1] Royal Holloway Univ London, Dept Econ, Egham TW20 0EX, Surrey, England
来源：
IEEE TRANSACTIONS ON INFORMATION THEORY | 2019年 / 65卷 / 01期
关键词：
Consistency; empirical process; ridge regression; reproducing kernel Hilbert space; universal consistency; METRIC ENTROPY; ASYMPTOTICS;
D O I：
10.1109/TIT.2018.2870373
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We consider stationary autoregressive processes with coefficients restricted to an ellipsoid. These are included in the family of autoregressive processes with absolutely summable coefficients. We provide consistency results under different norms for the estimation of such processes using constrained and penalized estimators. As an application, we show a weak form of universal consistency. Simulations show that directly including the constraint in the estimation can lead to results that are more robust.
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页码：538 / 550
页数：13
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