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I've seen somewhere that you can also build a regression for data gaps and just predict them. For example if we have data gaps in $x_{n}$, we can predict it through $x_{1},..,x_{n-1}$. But we will get multicollinearity then, which may break our model. So, how to use it correctly?

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