Bridge regression coefficient estimate $\hat{β}^{br}$ are the values that minimize the \begin{equation} \text{RSS} + \lambda \sum_{j=1}^p|\beta_j|^q , \end{equation} where $q \in \mathbb{R}$ and $q > 0 $.
My question is: why this kind of regression called BRIDGE regression?
I know that in 1993 Frank and Friedman proposed this in (1). However, at that time in that paper, there was no term like "bridge" nor "bridge regression". Confusingly, just 3 years later in 1996, Robert Tibshirani in the paper (2) cited the paper (1) using the term "bridge", viz., in section 11:
Frank and Friedman (1993) discuss a generalization of ridge regression and subset selection, through the addition of a penalty of the form $\lambda \sum_{j=1}^p|\beta_j|^q$ to the residual sum of squares. This is equivalent to a constraint of the form $\sum_{j}|\beta_j|^q \le t$; they called this the 'bridge'.
Emmm... They called? When the word "bridge" even do not occur in (1)?
I search on Google scholar and find no more paper before (2) citing (1), so where the word "bridge" come from? Do I miss something important?
I think my question might be related to Why is ridge regression called "ridge", why is it needed, and what happens when $\lambda$ goes to infinity?
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