I have a single output $y$, and multiple inputs $x_1, x_2,\dots,x_n$. I am running online(streaming) regression, which would be complicated with many inputs. So, to go around it, I want to have $n$ separate regressions: $y$ on $x_1$(simple OLS), then separately $y$ on $x_2, \dots$ then separately $y$ on $x_n$, and then I would weigh the outputs of these $n$ OLS regressions into one single output, by weighing them appropriately.
Is there a good way to go about this? I was thinking to weigh each regression by the absolute value of the correlation between $y$ and $x_i$, is this a good idea? Can anybody suggest alternatives, or relevant resources?