Abstract
Seemingly unrelated regression (SUR) models were applied when several linear regression equations were investigated at the same time. To reduce the multicollinearity influence in the SUR models, the one-parameter ridge (Ridge-1) solution was proposed and discussed by some researchers. As a generalization of the Ridge-1 solution, in the context of SUR models having multicollinearity problem, the two-parameter ridge (Ridge-2) solution was presented. Some simulations were performed to compare the proposed solution with the ordinary generalized least squares (GLS) and Ridge-1 solutions. Lastly, the proposed solution was applied on chronic renal failure effect data.
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