PC.robdist: Computes MCD distances.
In muschellij2/clever: Calculate Leverage of Component Models

Computes robust minimum covariance determinant (MCD) distances across the observations (rows). The MCD method selects a subset of h observations whose covariance matrix has minimum determinant across all subsets of size h. The MCD distances are Mahalanobis distances using the estimates of center (mean) and scale (covariance matrix) based on that subset.

1	PC.robdist(U)

`U`	An n x Q matrix of PC scores.

A list with components

robdist: A vector of length n of with the robust distance estimate for each observation.
inMCD: A vector of length n indicating if each observation is within the MCD subset.
Fparam: The estimated parameters of the F distribution of MCD distances.