# How can I estimate a “rank” dependent variable in a multivariate dataset?

I have a dataset where $x_{1}$, $x_{2}$, ..., $x_{k}$ are of mixed type and $y$ is a ranking from $1$ to $n$ where $n$ is the number of observations in the dataset. I'd like to predict $y$ based on the $x$s.

What is a good way to proceed here? My intuition is that a GLM approach won't be particularly useful given that $y$ is not independently distributed (although the $x$s are iid).

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