Robust Regression Appendix to An R and SPLUS Companion to Applied Regression JohnFox January Estimation Linear leastsquares estimates can behave badly when the error distribution is not normal partic
One remedy is to remove in57567uential observations from the leastsquares 64257t see Chapter 6 Section 61 in the text Another approach termed robust regression istoemploya64257tting criterion that is not as vulnerable as least squares to unusual dat
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