Ridge Autoregression Estimation: LS Method

A. K. MD. Ehsanes Saleh and Amal F. Ghania

Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 15, 3303-3320

Abstract: In an AR (p)-model, least-squares estimation of the parameters is considered when it is suspected that the parameters may belong to a linear subspace and the estimated covariance matrix is ill-conditioned. Accordingly, we define five estimators and study their properties in an asymptotic setup to discover dominance properties based on asymptotic distributional bias (ADB), MSE (ADMSE) matrices, and under quadratic risks (ADQR).

Date: 2015
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DOI: 10.1080/03610926.2013.857866

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