After reading about What is the best way to identify outliers in multivariate data? I noticed that some heuristics are hard to adapt to mult-variate analysis. I'm hoping there is a way to at least have a leverage vs residual plot. I have included an assortment of residual analysis plots to show what I mean.
The first 3 in this series can be adapted for multi-variate regression, they only require fitted, residual series to generate the plots. However the 4th (bottom right) plot seems tricky to adapt to multi-variate regression related plots.
Is there a way to do it? Could I put all of my data into a k*n long series? From which point I would and then proceed to standardize (0 mean, 1 stdv) and then square it add one and divide by n?
Let me know if there that approach has any potential flaws or if there is a better (more logical/sensible) way to reproduce plot #4.