Make diagnostic plot using the estimated PC subspace
mydiagPlot(x, obj, k, alpha = 0.5, co.sd = 0.25)the input data matrix
the returned output from rwltsspca
dimension of the PC subspace
the robust parameter which takes value between 0 to 0.5, default is 0.5
cutoff value for score outlier weight, default is 0.25
the diagnostics of outliers
the orthgonal distances with respect to the k-dimensional PC subspace
if the observation is outlying in the orthgonal complement of the PC subspace ws.od=0; otherwise ws.sd=1
the cutoff value for orthogonal distances
the score outlier weight, which is compared with 0.25 (by default) to flag score outliers
if the observation is outlying with the PC subspace ws.sd=0; otherwise ws.sd=1
the cutoff value for score outlier weight, default is 0.25
the retruned object when computing the score outlier weights