Description Usage Arguments Details Value
This function computes the matrices Q_i, such that outlier detection using Cook's distance is equivalent to \bigcap_{i \in [n]} y^T Q_i y ≥ 0.
1  constrInResponseCook(n, p, PX, PXperp, outlier.det, cutoff)

n, 
the number of observations. 
p, 
the number of variables, including the intercept. 
PX, 
the projection matrix onto the column space of the design matrix X. 
PXperp, 

outlier.det, 
indexes of detected outliers, can be empty. 
cutoff, 
the cutoff λ (see details). 
Using Cook's distance as a heuristic, the ith data is considered as an outlier if and only if its Cook's distance is larger than λ/n, where lambda is the userspecified cutoff. Then we can characterize this "detection event" as an intersection of quadratic constraints in the response y by \bigcap_{i \in [n]} y^T Q_i y ≥ 0.
This function returns a list of matrices Q_i.
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