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Print a nice “summary” about a numeric vector of robustness weights. Observations with weights around zero are marked as outliers.
summarizeRobWeights(w, digits = getOption("digits"), header = "Robustness weights:", eps = 0.1 / length(w), eps1 = 1e-3, ...)
none; the function is used for its side effect of printing.
numeric vector of robustness weigths.
digits to be used for printing.
print
string to be printed as header line.
numeric tolerance \(\epsilon\): values of w with \(\left|w_i\right| < \epsilon/n\) are said to be outliers.
w
numeric tolerance: values of w with \(\left|1 - w_i\right| < eps1\) are said to have weight ‘~= 1’.
~= 1
potential further arguments, passed to print().
print()
Martin Maechler
The summary methods for lmrob and glmrob make use of summarizeRobWeights().
summary
lmrob
glmrob
summarizeRobWeights()
Our methods for weights(), weights.lmrob(*, type="robustness") and weights.glmrob(*, type="robustness").
weights()
weights.lmrob(*, type="robustness")
weights.glmrob(*, type="robustness")
w <- c(1,1,1,1,0,1,1,1,1,0,1,1,.9999,.99999, .5,.6,1e-12) summarizeRobWeights(w) # two outside ~= {0,1} summarizeRobWeights(w, eps1 = 5e-5)# now three outside {0,1} ## See the summary() outputs
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